Methods and systems for monitoring, diagnosing, and treating chronic obstructive pulmonary disease

ABSTRACT

A novel set of 98 genes expressed in the respiratory tract epithelium that serve as biomarkers for measuring chronic obstructive pulmonary disease (COPD) activity are provided. Methods of classifying the (COPD) status of a subject are provided. Systems for expression-based classification of COPD disease status are provided. Methods of treating COPD are also provided, among other things.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 61/649,355, filed May 20, 2012, and U.S. Provisional PatentApplication No. 61/725,391, filed Nov. 12, 2012, which are herebyincorporated herein by reference.

GOVERNMENT FUNDING

This invention was made with Government Support under Contract Nos.HL095388 and RR025770 awarded by the National Institutes of Health. Thegovernment has certain rights in the invention.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has beensubmitted in ASCII format via EFS-Web and is hereby incorporated byreference in its entirety. Said ASCII copy, created on May 17, 2013, isnamed 1006_004_PCT.txt and is 1,147,697 bytes in size.

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) affects 14.8 millionindividuals in the United States alone (National Heart Lung and BloodInstitute. 2010. NHLBI Fiscal Year 2010 Fact Book) and is the thirdleading cause of death (Murphy S L, et al., 2012. Deaths: PreliminaryData for 2012. National Vital Statistics Reports 60). While biologicprocesses such as proteinase-antiproteinase imbalance, chronicinflammation, apoptosis and oxidative stress have been proposed to playa role in COPD pathogenesis, knowledge remains limited about how thesemolecular processes impact the clinical presentation and progression ofCOPD.

Genome-wide gene-expression profiling provides a powerful way to surveyCOPD-associated molecular alterations, but this approach has beenhindered by the limited availability of lung tissue samples fromindividuals with impaired lung function. As a result, studies ofwhole-genome gene-expression profiling of lung tissue in COPD (Spira A,et al. 2004. Gene Expression Profiling of Human Lung Tissue from Smokerswith Severe Emphysema. Am J Respir Cell Mol Biol 31:601-610; Golpon H A,et al. 2004. Emphysema Lung Tissue Gene Expression Profiling. Am JRespir Cell Mol Biol 31:595-600; Ning W, et al. 2004. Comprehensive geneexpression profiles reveal pathways related to the pathogenesis ofchronic obstructive pulmonary disease. Proc Natl Acad Sci USA101:14895-14900; Bhattacharya S, et al. 2009. Molecular biomarkers forquantitative and discrete COPD phenotyes. Am J Respir Cell Mol Biol40:359-367; Wang I M, et al,. 2008. Gene Expression Profiling inPatients with Chronic Obstructive Pulmonary Disease and Lung Cancer. AmJ Respir Crit Care Med 177:411.) have been limited by small sample sizesand confounding variables such as the presence of adjacent lung cancer.The development of a less invasive method for measuring COPD-associatedcellular and molecular processes would allow for the study of largecohorts and the potential for identifying molecular subtypes of COPD aswell as clinically-useful predictors of prognosis and response totherapy.

Alterations in airway epithelial gene expression among current andformer smokers that can serve as a tool for the early detection of lungcancer. Specifically, the expression levels of genes in cytologicallynormal large airway epithelial cells can serve as a sensitive andspecific diagnostic biomarker for lung cancer (Spira A, et al. 2007.Airway epithelial gene expression in the diagnostic evaluation ofsmokers with suspect lung cancer. Nat Med 13:361-366). Airway geneexpression also reflects PI3K pathway activation in smokers with airwayepithelial cell dysplasia that is reversible with the candidate lungcancer chemoprevention agent myo-inositol (Gustafson A M, et al. 2010.Airway PI3K pathway activation is an early and reversible event in lungcancer development. Sci Transl Med 2:26a25.). Importantly, PI3K is alsoactivated in tumors, suggesting that the airway can potentially serve asa surrogate for assessing some disease-associated processes. The impactof lung cancer on airway gene expression suggests that the airwayepithelium might also be impacted by other smoking-related diseases suchas COPD. Two small studies have demonstrated COPD-associated expressiondifferences in airway epithelium, but focused on the expression of alimited number of genes hypothesized to be involved in the pathogenesisof COPD (Pierrou S, et al. 2007. Expression of genes involved inoxidative stress responses in airway epithelial cells of smokers withchronic obstructive pulmonary disease. Am J Respir Crit Care Med175:577-586; Tilley A E, et al. 2009. Down-regulation of the Notchpathway in human airway epithelium in association with smoking andchronic obstructive pulmonary disease. Am J Respir Crit Care Med179:457-466.). Moreover, the relationship of these airway geneexpression changes to those that occur with COPD in lung tissue remainsunstudied ((Pierrou S, et al. 2007. Expression of genes involved inoxidative stress responses in airway epithelial cells of smokers withchronic obstructive pulmonary disease. Am J Respir Crit Care Med175:577-586; Tilley A E, et al. 2009. Down-regulation of the Notchpathway in human airway epithelium in association with smoking andchronic obstructive pulmonary disease. Am J Respir Crit Care Med179:457-466.), and it is unclear if the bronchial airway can be used asa more readily available biospecimen for identifying and measuring theactivity of distal COPD-associated processes to guide clinical decisionsin COPD management.

Accordingly, there is a need for new systems and methods and systems formonitoring, diagnosing, and treating COPD.

SUMMARY

Gene expression profiling of bronchial brushings obtained from currentand former smokers with and without COPD was performed as described inthe examples. Ninety-eight genes whose expression levels were associatedwith COPD status, FEV₁% predicted, and FEV₁/FVC were identified. Insilico analysis identified ATF4 as a potential transcriptional regulatorof genes with COPD-associated airway expression, and ATF4 overexpressionin airway epithelial cells in vitro recapitulated COPD-associated geneexpression changes. Genes with COPD-associated expression in thebronchial airway epithelium had similarly altered expression profiles inprior studies performed on small-airway epithelium and lung parenchyma,suggesting that transcriptomic alterations in the bronchial airwayepithelium reflect molecular events found at more distal sites ofdisease activity. Many of the airway COPD-associated gene expressionchanges revert toward baseline following therapy with the inhaledcorticosteroid fluticasone in independent cohorts. The findings reportedin the examples demonstrate a molecular field of injury throughout thebronchial airway of active and former smokers with COPD that may bedriven in part by modulation of ATF4 and is modifiable with therapy.These results demonstrate the novel finding that expression of the 98identified genes in the airway epithelium serve biomarkers for measuringbiomarkers of COPD disease activity for guiding clinical management ofCOPD and other uses described herein.

Accordingly, this disclosure provides methods of classifying the chronicobstructive pulmonary disease (COPD) status of a subject. The methodsmay comprise (a) providing a tissue sample obtained from the respiratorytract epithelium of the subject; (b) determining the expression level ofat least one transcript comprising (i) a sequence as set forth in anyone of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100 nucleotidesof a sequence as set forth in any one of SEQ ID NOS. 1 to 98, or (iii) asequence with substantial homology to (i) or (ii), in the tissue sampleto provide an expression pattern profile; (c) comparing the expressionpattern profile with a reference expression pattern profile; and (d)classifying the COPD status of the subject based on the comparing.

In some embodiments of the methods the tissue sample is a tissue sampleobtained from the bronchi walls of at least one of sixth generation,seventh generation, and eighth generation bronchi of the subject. Insome embodiments of the methods the tissue sample is obtained duringfiberoptic bronchoscopy by brushing the bronchi walls of the subject.

In some embodiments of the methods the at least one transcript is atranscript that is upregulated in COPD and is selected from SEQ ID NO:6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO:13, SEQ ID NO: 14, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ IDNO: 19, SEQ ID NO: 20, SEQ ID NO: 22, SEQ ID NO: 26, SEQ ID NO: 27, SEQID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33,SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO:39, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 45, SEQ ID NO: 46, SEQ IDNO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 55, SEQ ID NO: 56, SEQID NO: 57, SEQ ID NO: 59, SEQ ID NO: 63, SEQ ID NO: 64, SEQ ID NO: 65,SEQ ID NO: 66, SEQ ID NO: 68, SEQ ID NO: 71, SEQ ID NO: 72, SEQ ID NO:73, SEQ ID NO: 74, SEQ ID NO: 78, SEQ ID NO: 81, SEQ ID NO: 82, SEQ IDNO: 84, SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID NO: 94, SEQ ID NO: 96, andSEQ ID NO: 98.

In some embodiments of the methods the at least one transcript is atranscript that is downregulated in COPD and is selected from SEQ ID NO:1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 9,SEQ ID NO: 11, SEQ ID NO: 15, SEQ ID NO: 21, SEQ ID NO: 23, SEQ ID NO:24, SEQ ID NO: 25, SEQ ID NO: 29, SEQ ID NO: 36, SEQ ID NO: 40, SEQ IDNO: 41, SEQ ID NO: 44, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, SEQID NO: 50, SEQ ID NO: 54, SEQ ID NO: 58, SEQ ID NO: 60, SEQ ID NO: 61,SEQ ID NO: 62, SEQ ID NO: 67, SEQ ID NO: 69, SEQ ID NO: 70, SEQ ID NO:75, SEQ ID NO: 76, SEQ ID NO: 77, SEQ ID NO: 79, SEQ ID NO: 80, SEQ IDNO: 83, SEQ ID NO: 85, SEQ ID NO: 88, SEQ ID NO: 89, SEQ ID NO: 90, SEQID NO: 91, SEQ ID NO: 92, SEQ ID NO: 93, SEQ ID NO: 95, SEQ ID NO: 97.

In some embodiments the methods comprise determining the expressionlevel of at least ten transcripts, each comprising (i) a sequence as setforth in any one of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100nucleotides of a sequence as set forth in any one of SEQ ID NOS. 1 to98, or (iii) a sequence with substantial homology to (i) or (ii), in thetissue sample to provide the expression pattern profile. In someembodiments of the methods comprise determining the expression level ofat least 98 transcripts, each comprising (i) a sequence as set forth inany one of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100nucleotides of a sequence as set forth in any one of SEQ ID NOS. 1 to98, or (iii) a sequence with substantial homology to (i) or (ii), in thetissue sample to provide the expression pattern profile. In someembodiments the expression level of a plurality of transcripts isdetermined. In some embodiments the expression level of from 1-5, 5-10,5-20, 10-25, 20-40, 30-50, 50-75, or all 98 transcripts is determined.

In some embodiments of the methods an increased relative level ofexpression of the at least one transcript in the respiratory tractepithelium sample of the subject, a decreased relative level of the atleast one transcript in the respiratory tract epithelium sample of thesubject, or a combination thereof is used to classify the COPD.

In some embodiments of the methods the COPD status of the subject isclassified as to the extent of at least one of airflow obstruction,emphysematous descruction of lung parenchyma, and small airwayinflammation in the subject. In some embodiments of the methods the COPDstatus of the subject is classified as the the likelihood of diseaseprogression. In some embodiments of the methods the COPD status of thesubject is classified as to current disease severity. In someembodiments of the methods the COPD status of the subject is classifiedas to the likelihood of a positive clinical response to treatment withan anti-COPD therapeutic agent. In some embodiments of the methods theCOPD status of the subject is classified as to the clinical response ofthe subject to treatment with an anti-COPD therapeutic agent.

In some embodiments of the methods the expression level of the at leastone transcript is determined by a process comprising a method selectedfrom RT-PCR, Northern blotting, ligase chain reaction, and arrayhybridization.

In some embodiments the methods further comprise measuring theexpression level of at least one control nucleic acid in the tissuesample.

In some embodiments of the methods the expression level of the at leastone transcript is determined by a process comprising patternrecognition. In some embodiments the process comprising patternrecognition comprises a linear combination of expression levels of thetarget transcripts. In some embodiments of the process comprisingpattern recognition comprises a nonlinear combination of expressionlevels of the target sequences. In some embodiments of the processcomprising pattern recognition comprises a nonlinear combination ofexpression levels of the target sequences.

This disclosure also provides systems for expression-basedclassification of COPD disease status. The system comprises at least onepolynucleotide capable of specifically hybridizing to a RNA transcriptcomprising (i) a sequence as set forth in any one of SEQ ID NOS. 1 to98, (ii) a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS. 1 to 98, (iii) a sequence withsubstantial homology to (i) or (ii), or (iv) a sequence that is thecomplement of a sequence according to any one of (i) to (iii).

In some embodiments of the systems the at least one polynucleotidecomprises at least one polynucleotide probe for the detection of thetranscript. In some embodiments of the systems the at least onepolynucleotide comprises at least one primer pair capable of amplifyinga portion of the RNA transcript. In some embodiments the systemcomprises polynucleotides comprising sequences as set forth in SEQ IDNOs: 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10. In some embodiments the systemcomprises at least 5 polynucleotides. In some embodiments the systemsystem comprises at least 10 polynucleotides.

In some embodiments of the systems the at least one polynucleotidecomprises a sequence corresponding to one or more nucleic acid moleculesselected from: (a) a nucleic acid depicted in any one of SEQ ID NOs:1-98; (b) an RNA form of any one of the nucleic acids depicted in SEQ IDNOs: 1-98; (c) a peptide nucleic acid form of any one of the nucleicacids depicted in SEQ ID NOs: 1-98; (d) a nucleic acid comprising atleast 20 consecutive bases of any of (a-c); (e) a nucleic acidcomprising at least 25 consecutive bases having at least 90% sequenceidentity to any of (a-c); and (f) a complement to any of (a-e).

This disclosure also provides methods of treating COPD in a subject inneed thereof. The methods comprise (a) providing a tissue sampleobtained from the respiratory tract epithelium of the subject; (b)determining the expression level of at least one transcript comprising(i) a sequence as set forth in any one of SEQ ID NOS. 1 to 98, (ii) afragment of at least 100 nucleotides of a sequence as set forth in anyone of SEQ ID NOS. 1 to 98, or (iii) a sequence with substantialhomology to (i) or (ii), in the tissue sample to provide an expressionpattern profile; (c) comparing the expression pattern profile with areference expression pattern profile; (d) classifying the COPD status ofthe subject based on the comparing; (e) administering an anti-COPDtherapeutic agent to the subject if the subject is classified as havingactive COPD disease status warranting therapeutic intervention; and/or(f) not administering an anti-COPD therapeutic agent to the subject ifthe subject is classified as not having active COPD disease statuswarranting therapeutic intervention.

In some embodiments of the methods the tissue sample is a tissue sampleobtained from the bronchi walls of at least one of sixth generation,seventh generation, and eighth generation bronchi of the subject. Insome embodiments of the methods the tissue sample is obtained duringfiberoptic bronchoscopy by brushing the bronchi walls of the subject.

In some embodiments of the methods the at least one transcript is atranscript that is upregulated in COPD and is selected from SEQ ID NO:6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO:13, SEQ ID NO: 14, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ IDNO: 19, SEQ ID NO: 20, SEQ ID NO: 22, SEQ ID NO: 26, SEQ ID NO: 27, SEQID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33,SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO:39, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 45, SEQ ID NO: 46, SEQ IDNO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 55, SEQ ID NO: 56, SEQID NO: 57, SEQ ID NO: 59, SEQ ID NO: 63, SEQ ID NO: 64, SEQ ID NO: 65,SEQ ID NO: 66, SEQ ID NO: 68, SEQ ID NO: 71, SEQ ID NO: 72, SEQ ID NO:73, SEQ ID NO: 74, SEQ ID NO: 78, SEQ ID NO: 81, SEQ ID NO: 82, SEQ IDNO: 84, SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID NO: 94, SEQ ID NO: 96, andSEQ ID NO: 98.

In some embodiments of the methods the at least one transcript is atranscript that is downregulated in COPD and is selected from SEQ ID NO:1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 9,SEQ ID NO: 11, SEQ ID NO: 15, SEQ ID NO: 21, SEQ ID NO: 23, SEQ ID NO:24, SEQ ID NO: 25, SEQ ID NO: 29, SEQ ID NO: 36, SEQ ID NO: 40, SEQ IDNO: 41, SEQ ID NO: 44, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, SEQID NO: 50, SEQ ID NO: 54, SEQ ID NO: 58, SEQ ID NO: 60, SEQ ID NO: 61,SEQ ID NO: 62, SEQ ID NO: 67, SEQ ID NO: 69, SEQ ID NO: 70, SEQ ID NO:75, SEQ ID NO: 76, SEQ ID NO: 77, SEQ ID NO: 79, SEQ ID NO: 80, SEQ IDNO: 83, SEQ ID NO: 85, SEQ ID NO: 88, SEQ ID NO: 89, SEQ ID NO: 90, SEQID NO: 91, SEQ ID NO: 92, SEQ ID NO: 93, SEQ ID NO: 95, SEQ ID NO: 97.

In some embodiments the methods comprise determining the expressionlevel of at least ten transcripts, each comprising (i) a sequence as setforth in any one of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100nucleotides of a sequence as set forth in any one of SEQ ID NOS. 1 to98, or (iii) a sequence with substantial homology to (i) or (ii), in thetissue sample to provide the expression pattern profile. In someembodiments the methods comprise determining the expression level of atleast 98 transcripts, each comprising (i) a sequence as set forth in anyone of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100 nucleotidesof a sequence as set forth in any one of SEQ ID NOS. 1 to 98, or (iii) asequence with substantial homology to (i) or (ii), in the tissue sampleto provide the expression pattern profile. In some embodiments theexpression level of a plurality of transcripts is determined. In someembodiments the expression level of from 1-5, 5-10, 5-20, 10-25, 20-40,30-50, 50-75, or all 98 transcripts is determined.

In some embodiments of the methods an increased relative level ofexpression of the at least one transcript in the respiratory tractepithelium sample of the subject, a decreased relative level of the atleast one transcript in the respiratory tract epithelium sample of thesubject, or a combination thereof is used to classify the COPD.

In some embodiments of the methods the COPD status of the subject isclassified as to the extent of at least one of airflow obstruction,emphysematous descruction of lung parenchyma, and small airwayinflammation in the subject. In some embodiments of the methods the COPDstatus of the subject is classified as the the likelihood of diseaseprogression. In some embodiments of the methods the COPD status of thesubject is classified as to current disease severity. In someembodiments of the methods the COPD status of the subject is classifiedas to the likelihood of a positive clinical response to treatment withan anti-COPD therapeutic agent. In some embodiments of the methods theCOPD status of the subject is classified as to the clinical response ofthe subject to treatment with an anti-COPD therapeutic agent.

In some embodiments of the methods the expression level of the at leastone transcript is determined by a process comprising a method selectedfrom RT-PCR, Northern blotting, ligase chain reaction, and arrayhybridization.

In some embodiments the methods further comprise measuring theexpression level of at least one control nucleic acid in the tissuesample.

In some embodiments of the methods the expression level of the at leastone transcript is determined by a process comprising patternrecognition. In some embodiments the process comprising patternrecognition comprises a linear combination of expression levels of thetarget transcripts. In some embodiments the process comprising patternrecognition comprises a nonlinear combination of expression levels ofthe target sequences.

In some embodiments the process comprising pattern recognition comprisesa nonlinear combination of expression levels of the target sequences.

In some embodiments of the methods the anti-COPD therapeutic agent isfluticasone.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating the flow of samples in the primarycohort (GSE37147) and the GLUCOLD study (GSE36221).

FIGS. 2-1 to 2-8 show a semi-supervised heatmap of the 98 genesassociated with COPD and continuous measures of lung function. A totalof 107 genes were associated with COPD, 110 genes with FEV1% predicted,and 101 genes with FEV1/FVC (FDR<0.05, FC>1.25). 98 genes were in commonto all of these measures. These results demonstrate that airwayepithelial gene expression reflects the presence of COPD and theseverity of lung function impairment.

FIG. 3 (shows that lung tissue gene expression associated withCOPD-related phenotypes is concordant with the airway epithelial geneexpression signature of COPD. COPD-associated gene expression inpreviously published datasets was compared to the bronchial airway COPDsignature. The color bar indicates the strength of association of geneexpression in the previously published datasets with COPD-relatedphenotypes. The position of each vertical bar indicates the position ofa gene from the COPD airway gene expression signature within the rankedlist. The height of this bar represents the running GSEA enrichmentscore. This analysis identified concordant enrichment of the bronchialairway COPD signature among previously published COPD gene expressiondatasets (FDR<0.05).

FIG. 4 presents a validation of genes within the bronchial airway COPDsignature. A total of nine genes were selected for validation by RT-PCR.For each of the nine genes, the bar plots show the mean and standarderror of the log2-gene expression level as measured by microarray(left), and the relative expression as measured by qRT-PCR.

FIGS. 5A to 5C show that ATF4 overexpression in BEAS2B cells in vitrorecapitulates the in vivo airway gene-expression signature of COPD. A)GSEA demonstrates enrichment of genes with increased expression inairway epithelium from individuals with COPD among genes whoseexpression is increased with ATF4 overexpression in BEAS2B cells(FDR<0.05). Genes are ranked from left to right based on theirATF4-associated expression pattern in vitro. The position of eachvertical bar indicates the position of a gene with COPD-associated geneexpression in airway epithelium within this ranked list. The height ofthis bar represents the running GSEA enrichment score. Core enrichmentgenes are highlighted in green. B) Expression levels of the coreenrichment genes (green) in the bronchial brushing samples, all of whichare predicted targets of ATF4 (p<0.001), are shown in this heatmapsupervised by COPD status (orange: COPD; blue: Normal). C) Expressionlevels of the core enrichment genes (green) with ATF4 overexpression inairway epithelium in vitro (black: negative control; yellow: ATF4overexpression).

FIG. 6 presents confirmation of in vitro ATF4 overexpression in culturedairway epithelial cells. qRT-PCR was used to confirm successfultransfection and overexpression of ATF4 in BEAS2B cells. The bar plotsillustrate the relative expression and standard error of ATF4 and one ofits predicted downstream targets, ATF3.

FIG. 7 shows that airway epithelial gene expression associated with COPDis concordant with previously published microarray datasets of COPD lungtissue. Airway gene expression associated with COPD was compared to genelists identified in previous studies of lung tissue gene expression inCOPD using GSEA. The color bar indicates the strength of association ofairway epithelial gene expression with COPD as measured by thet-statistic for the COPD term after adjusting for covariates. Theposition of each vertical bar from left to right indicates the positionof a gene from one of the previously published lung parenchyma gene sets(genes whose expression was previously identified to be associated witha COPD-related trait) within the ranked airway gene list. The height ofthis bar represents the running GSEA enrichment score. This analysisidentified concordant enrichment of previously reported COPD-associatedgene expression changes in lung tissue and COPD-associated changes ingene expression in the bronchial airway (FDR<0.05), and suggests thatthere is a common COPD effect in both tissues.

FIGS. 8A to 8C show that airway transcriptomic alterations in COPDreflect gene-expression changes associated with emphysema severity inlung tissue. A) GSEA demonstrates enrichment of genes whose expressionlevels in the airway epithelium significantly increased in COPD amonggenes whose expression is increased with worsening emphysema severity inlung tissue (FDR<0.05). Genes are ranked from left to right based ontheir emphysema-associated expression pattern in lung tissue. Theposition of each vertical bar indicates the position of a gene whoseexpression in airway epithelium is associated with COPD within thisranked list. The height of this bar represents the running GSEAenrichment score. The core enrichment genes are highlighted in green. B)Expression of the core enrichment genes (green) in the bronchialbrushing samples is shown in this heatmap supervised by COPD status(orange: COPD; blue: Normal). C) Expression of the core enrichment genes(green) in lung tissue samples is shown in this heatmap supervised byemphysema severity (light grey: no emphysema; black: severe emphysema).

FIGS. 9A and 9B show that gene expression changes in the airway ofsubjects with COPD are modulated by inhaled corticosteroids. A) UsingGSEA, we identified enrichment of airway gene expression associated withCOPD in an independent gene expression dataset of endobronchial biopsiesobtained at 0, 6, and 30 months from individuals with COPD randomized toreceive fluticasone (n=25), salmeterol and fluticasone (n=20), orplacebo (n=23). Many genes increased in COPD decreased with fluticasone,and genes decreased in COPD increased with fluticasone. Genes are rankedfrom left to right based on their association with the time by treatmentinteraction effect. The position of each vertical bar indicates theposition of a gene whose expression in airway epithelium is associatedwith COPD within this ranked list (the upper plot includes genesincreased in COPD; while the lower plot includes genes decreased inCOPD). The height of this bar represents the running GSEA enrichmentscore. B) Boxplots illustrate the expression levels of three coreenrichment genes in the bronchial airway epithelium of subjects withCOPD (n=87) compared to subjects without COPD (n=151) and in anindependent cohort of subjects randomized to receivefluticasone-containing therapies or placebo (n=55 subjects with ≧1timepoint). The y-axis represents the z-score normalized residual matrixafter adjusting for RIN, treatment, time, and patient effect.

FIG. 10 shows modulation of the bronchial airway gene expressionsignature of COPD by fluticasone. Fluticasone-associated changes inbronchial airway epithelial gene expression was compared to thebronchial airway COPD signature. Genes are ranked from left to rightbased on their association with the time and treatment interactioneffect, and the color bar indicates the strength of this association.Each vertical bar indicates the position of a gene from the COPD airwaygene expression signature within the ranked list, and the height of thisbar represents the running GSEA enrichment score. These findingsdemonstrate that the airway COPD signature can be modulated byfluticasone (FDR<0.05).

DETAILED DESCRIPTION A. Introduction

The present disclosure provides systems and methods for classifying COPDin a subject, which allows for the diagnosis of COPD in the subject. Thesystems and methods are based on the identification of expressedtranscripts that are differentially expressed in the airway of subjectswith COPD relative to normal subjects. These expressed transcripts canbe considered as a library which can be used as a resource for theidentification of sets of specific target sequences (“COPDclassification sets”), which may represent the entire library ofexpressed transcripts or a subset of the library and the detection ofwhich is indicative of the status of COPD in a subject. The disclosurefurther provides for probes capable of detecting these target sequencesand primers that are capable of amplifying the target sequences.

In accordance with some embodiments, the target sequences comprised bythe COPD classification set are sequences based on or derived from thegene transcripts from the library, or a subset thereof. Such sequencesare occasionally referred to herein as “probe selection regions” or“PSRs.” In some embodiments, the target sequences comprised by the COPDclassification set are sequences based on the gene transcripts from thelibrary, or a subset thereof, and include both coding and non-codingsequences.

The methods employ molecular analysis of the expression levels of one ormore transcripts corresponding to SEQ ID NOs:1 to 98. Subsets andcombinations of these transcripts may be used as described herein. Insome embodiments, the systems and methods provide for the molecularanalysis of the expression levels of one or more of the target sequencesas set forth in SEQ ID NOs: 1-98. Subsets and combinations of thesetarget sequences or probes complementary thereto may be used asdescribed herein.

In some embodiments, the subset includes non-canonical expressedtranscripts.

In some embodiments, the subset includes at least one transcript, eachof the at least one transcripts comprising a non-coding sequence as setforth in any one of SEQ ID NOS: 1-98.

Before the present disclosure is described in further detail, it is tobe understood that the inventions disclosed herein are not limited tothe particular methodology, compositions, articles or machinesdescribed, as such methods, compositions, articles or machines can, ofcourse, vary. It is also to be understood that the terminology usedherein is for the purpose of describing particular embodiments only, andis not intended to limit the scope of the disclosure or the disclosedinventions.

B. Definitions and Terminology

Unless otherwise defined herein, scientific and technical terms used inconnection with the present disclosure shall have the meanings that arecommonly understood by those of ordinary skill in the art. Further,unless otherwise required by context, singular terms shall include theplural and plural terms shall include the singular. Generally,nomenclatures used in connection with, and techniques of, biochemistry,enzymology, molecular and cellular biology, microbiology, genetics andprotein and nucleic acid chemistry and hybridization described hereinare those well-known and commonly used in the art. Certain referencesand other documents cited herein are expressly incorporated herein byreference. Additionally, all UniProt/SwissProt records cited herein arehereby incorporated herein by reference. In case of conflict, thepresent specification, including definitions, will control. Thematerials, methods, and examples are illustrative only and not intendedto be limiting.

The methods and techniques of the present disclosure are generallyperformed according to conventional methods well known in the art and asdescribed in various general and more specific references that are citedand discussed throughout the present specification unless otherwiseindicated. See, e.g., Sambrook et al., Molecular Cloning: A LaboratoryManual, 3d ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor,N.Y. (2001); Ausubel et al., Current Protocols in Molecular Biology,Greene Publishing Associates (1992, and Supplements to 2002); Taylor andDrickamer, Introduction to Glycobiology, Oxford Univ. Press (2003);Worthington Enzyme Manual, Worthington Biochemical Corp., Freehold,N.J.; Handbook of Biochemistry: Section A Proteins, Vol I, CRC Press(1976); Handbook of Biochemistry: Section A Proteins, Vol II, CRC Press(1976); Essentials of Glycobiology, Cold Spring Harbor Laboratory Press(1999).

This disclosure refers to sequence database entries (e.g., Entrezgene IDidentifiers) for certain protein and gene sequences that are publishedon the internet and maintained in public databases known to and used bythose of skill in the art, as well as other information on the internet.The skilled artisan understands that information on the internet,including sequence database entries, is updated from time to time andthat, for example, the reference number used to refer to a particularsequence can change. Where reference is made to a public database ofsequence information or other information on the internet, it isunderstood that such changes can occur and particular embodiments ofinformation on the internet can come and go. Because the skilled artisancan find equivalent information by searching on the internet, areference to an internet web page address or a sequence database entryevidences the availability and public dissemination of the informationin question.

Before the present proteins, compositions, methods, and otherembodiments are disclosed and described, it is to be understood that theterminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. It must be notedthat, as used in the specification and the appended claims, the singularforms “a,” “an” and “the” include plural referents unless the contextclearly dictates otherwise.

The terms “comprising” and “having” as used herein are synonymous witheach other and “including” or “containing”, and are inclusive oropen-ended and do not exclude additional, unrecited members, elements ormethod steps

The term “polynucleotide” as used herein refers to a polymer of greaterthan one nucleotide in length of ribonucleic acid (RNA),deoxyribonucleic acid (DNA), hybrid RNA/DNA, modified RNA or DNA, or RNAor DNA mimetics, including peptide nucleic acids (PNAs). Thepolynucleotides may be single- or double-stranded. The term includespolynucleotides composed of naturally-occurring nucleobases, sugars andcovalent internucleoside (backbone) linkages as well as polynucleotideshaving non-naturally-occurring portions which function similarly. Suchmodified or substituted polynucleotides are well-known in the art andfor the purposes of this disclosure, are referred to as “analogues.”

“Complementary” or “substantially complementary” refers to the abilityto hybridize or base pair between nucleotides or nucleic acids, such as,for instance, between a sensor peptide nucleic acid or polynucleotideand a target polynucleotide. Complementary nucleotides are, generally, Aand T (or A and U), or C and G. Two single-stranded polynucleotides orPNAs are said to be substantially complementary when the bases of onestrand, optimally aligned and compared and with appropriate insertionsor deletions, pair with at least about 80% of the bases of the otherstrand, in some embodiments at least about 90% to 95%, and in someembodiments at least about 95%, 96%, 97%, 98%, 99%, up to 100%.

Alternatively, substantial complementarity exists when a polynucleotidewill hybridize under selective hybridization conditions to itscomplement. Typically, selective hybridization will occur when there isat least about 65% complementarity over a stretch of at least 14 to 25bases, for example at least about 75%, or at least about 90%complementarity. See, M. Kanehisa Nucleic Acids Res. 12:203 (1984).

“Preferential binding” or “preferential hybridization” refers to theincreased propensity of one polynucleotide to bind to its complement ina sample as compared to a noncomplementary polymer in the sample.

Hybridization conditions will typically include salt concentrations ofless than about 1M, more usually less than about 500 mM, for exampleless than about 200 mM. In the case of hybridization between a peptidenucleic acid and a polynucleotide, the hybridization can be done insolutions containing little or no salt. Hybridization temperatures canbe as low as 5° C., but are typically greater than 22° C., such asgreater than about 30° C., for example in excess of about 37° C. Longerfragments may require higher hybridization temperatures for specifichybridization as is known in the art. Other factors may affect thestringency of hybridization, including base composition and length ofthe complementary strands, presence of organic solvents and extent ofbase mismatching, and the combination of parameters used is moreimportant than the absolute measure of any one alone. Otherhybridization conditions which may be controlled include buffer type andconcentration, solution pH, presence and concentration of blockingreagents to decrease background binding such as repeat sequences orblocking protein solutions, detergent type(s) and concentrations,molecules such as polymers which increase the relative concentration ofthe polynucleotides, metal ion(s) and their concentration(s),chelator(s) and their concentrations, and other conditions known in theart.

“Multiplexing” herein refers to an assay or other analytical method inwhich multiple analytes can be assayed simultaneously.

A “target sequence as used herein (also occasionally referred to as a“PSR” or “probe selection region”) refers to a region of the genomeagainst which one or more probes can be designed. As used herein, aprobe is any polynucleotide capable of selectively hybridizing to atarget sequence or its complement, or to an RNA version of either. Aprobe may comprise ribonucleotides, deoxyribonucleotides, peptidenucleic acids, and combinations thereof. A probe may optionally compriseone or more labels. In some embodiments, a probe may be used to amplifyone or both strands of a target sequence or an RNA form thereof, actingas a sole primer in an amplification reaction or as a member of a set ofprimers.

“Administer” refers to the placement of a composition into a subject bya method or route which results in at least partial localization of thecomposition at a desired site such that desired effect is produced. Acompound or composition described can be administered by any appropriateroute known in the art including, but not limited to, oral or parenteralroutes, including intravenous, intramuscular, subcutaneous, transdermal,airway (aerosol), pulmonary, nasal, rectal, and topical (includingbuccal and sublingual) administration.

Exemplary modes of administration include, but are not limited to,injection, infusion, instillation, inhalation, or ingestion. “Injection”includes, without limitation, intravenous, intramuscular, intraarterial,intrathecal, intraventricular, intracapsular, intraorbital,intracardiac, intradermal, intraperitoneal, transtracheal, subcutaneous,subcuticular, intraarticular, sub capsular, subarachnoid, intraspinal,intracerebrospinal, and intrasternal injection and infusion. In someembodiments, the compositions are administered by intravenous infusionor injection.

As used herein the terms “treat,” “treatment,” and the like, refer to adecrease in severity, indicators, symptoms, or markers of COPD. In thecontext of the present disclosure insofar as it relates to any of theconditions recited herein, the terms “treat,” “treatment,” and the likemean to relieve, alleviate, ameliorate, inhibit, slow down, reverse, orstop the progression, aggravation, deterioration, progression,anticipated progression or severity of at least one symptom orcomplication associated with COPD. In some embodiments, the symptoms ofCOPD are alleviated by at least 5%, at least 10%, at least 20%, at least30%, at least 40%, or at least 50%.

As used herein, a “subject” means a human or animal. Typically, thesubject is a mammal. The mammal can be a human, non-human primate,mouse, rat, dog, cat, horse, or cow, but are not limited to theseexamples. Mammals other than humans can be advantageously used, forexample, as subjects that represent animal models of COPD, for example.In addition, the methods, systems and other aspects described herein canbe used to classify and/or treat domesticated animals and/or pets. Asubject can be male or female. A subject can be one who has beenpreviously diagnosed with or identified as suffering from or having COPDor one or more complications related to COPD, and optionally, but neednot have already undergone treatment for COPD or the one or morecomplications related to COPD. A subject can also be one who is notsuffering from COPD. A subject can also be one who has been diagnosed ashaving an above average likelihood of developing COPD or one or morecomplications related to COPD. It can include one who shows improvementsin known COPD risk factors as a result of receiving one or moretreatments for COPD or one or more complications related to COPD.Alternatively, a subject can also be one who has not been previouslydiagnosed as having COPD or one or more complications related to COPD.For example, a subject can be one who exhibits one or more risk factorsfor COPD or one or more complications related to COPD, or a subject whodoes not exhibit COPD risk factors, or a subject who is asymptomatic forCOPD or one or more complications related to COPD. A subject can also beone who is suffering from or at risk of developing COPD or one or morecomplications related to COPD. A subject can also be one who has beendiagnosed with or identified as having one or more complications relatedto COPD, or alternatively, a subject can be one who has not beenpreviously diagnosed with or identified as having one or morecomplications related to COPD.

The term “chronic obstructive pulmonary disease” or “COPD” is generallyapplied to chronic respiratory disease processes characterized by thepersistent obstruction of bronchial air flow. COPD patients can sufferfrom conditions such as bronchitis, cystic fibrosis, asthma oremphysema.

As used herein, the term “respiratory tract epithelium” refers toepithelium from anywhere in the upper respiratory tract or respiratoryairways. The term specifically excludes lung tissue. Thus, the termincludes epithelium from the nose, mouth, nasal passages, paranasalsinuses, pharynx, larynx, trachea, bronchi and bronchioles. In someembodiments the term may include epithelium from one, two, three, four,five, six, seven, eight, or all of the nose, mouth, nasal passages,paranasal sinuses, pharynx, larynx, trachea, bronchi and bronchioles. Insome embodiments respiratory tract epithelium is specified as epitheliumfrom the mouth. In some embodiments respiratory tract epithelium isspecified as epithelium from the nose. In some embodiments respiratorytract epithelium is specified as epithelium from the trachea. In someembodiments respiratory tract epithelium is specified as epithelium fromthe bronchi. In some embodiments respiratory tract epithelium isspecified as epithelium from at least one of the sixth generation,seventh generation, and eighth generation bronchi. Because the term“respiratory tract epithelium” specifically excludes lung tissue itexcludes tissue from any of the respiratory bronchioles, alveolar ducts,alveolar sacs, and alveoli.

As used herein, an “anti-COPD therapeutic” refers to any molecule usedtreat COPD. Non-limiting examples include bronchodilators (e.g. shortand long acting β-2 stimulants), orally administered bronchodilators,anti-cholinergic agents (e.g. ipratoprium bromide, theophyllinecompounds or a combination), inhaled anti-cholinergic agents, steroids(oral or topical), corticosteroids, fluticasone, mucolytic agents (e.g.,ambroxol, ergosterin, carbocysteine, iodinated glycerol), antibiotics,antifungals, moisterization by nebulization, anti-tussives, respiratorystimulants (e.g., doxapram, almitrine bismesylate), a-1 antitrypsinadministration, fromoterol, budesonide, and/or fromoterol/budesonidecombination therapy. In some embodiments the anti-COPD therapeutic agentis a GHK tripeptide in any form. GHK is comprised of aGlycine-Histidine-Lysine tripeptide. GHK may be synthesized by methodsfamiliar to those skilled in the art or purchased commercially. GHKtripeptides are described in WO2012/129237A2, which is herebyincorporated herein by reference.

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where the event or circumstance occurs and instances in whichit does not.

As used herein, the term “about” refers to approximately a +/−10%variation from a given value. It is to be understood that such avariation is always included in any given value provided herein, whetheror not it is specifically referred to.

Terms such as “connected,” “attached,” “linked” and “conjugated” areused interchangeably herein and encompass direct as well as indirectconnection, attachment, linkage or conjugation unless the contextclearly dictates otherwise.

As used herein, “classifying the COPD status” of a subject includeswithout limitation, determining that the subject has an increasedlikelihood of currently suffering from COPD or that the subjectcurrently does suffer from COPD, determining that the subject does nothave an increased likelihood of currently suffering from COPD or thatthe subject currently does not suffer from COPD, determining that thesubject has an increased risk of developing COPD in the future, anddetermining that the subject does not have an increased risk ofdeveloping COPD in the future. The term also includes determining that asubject is more or less likely to respond to a particular course oftherapeutic intervention such as without limitation a course oftreatment with a an anti-COPD therapeutic agent. As a skilled artisanwill appreciate, the term includes all forms of diagnosing COPD and/orthe symptoms of COPD and of prognosis of subjects who suffer from COPD.

Where a range of values is recited, it is to be understood that eachintervening integer value, and each fraction thereof, between therecited upper and lower limits of that range is also specificallydisclosed, along with each subrange between such values. The upper andlower limits of any range can independently be included in or excludedfrom the range, and each range where either, neither or both limits areincluded is also encompassed by the disclosure. Where a value beingdiscussed has inherent limits, for example where a component can bepresent at a concentration of from 0 to 100%, or where the pH of anaqueous solution can range from 1 to 14, those inherent limits arespecifically disclosed. Where a value is explicitly recited, it is to beunderstood that values which are about the same quantity or amount asthe recited value are also within the scope of the disclosure, as areranges based thereon. Where a combination is disclosed, eachsubcombination of the elements of that combination is also specificallydisclosed and is within the scope of the disclosure. Conversely, wheredifferent elements or groups of elements are disclosed, combinationsthereof are also disclosed. Where any element of is disclosed as havinga plurality of alternatives, examples of that element in which eachalternative is excluded singly or in any combination with the otheralternatives are also hereby disclosed; more than one element of anembodiment can have such exclusions, and all combinations of elementshaving such exclusions are hereby disclosed.

C. COPD Classification System

The systems of the present disclosure are based on the identification ofa library of gene transcripts (COPD classification library) that aredifferentially expressed in the respiratory tract epithelium of subjectshaving a COPD disease state in their lung tissue relative to therespiratory tract epithelium of subjects having healthy lung tissue, andthus may be diagnostic for COPD disease state. For example, relativeover and/or under expression of one or more of the gene transcripts inan airway tissue sample compared to a reference sample or expressionprofile or signature there from may be indicative of a COPD diseasestate. The reference sample can be, for example, from the respiratorytract epithelium of a subject having healthy lung tissue. The referenceexpression profile or signature may optionally be normalized to one ormore appropriate reference gene transcripts. Alternatively or inaddition to, expression of one or more of the gene transcripts in arespiratory tract epithelium sample may be compared to an expressionprofile or signature from one or more known COPD respiratory tractepithelium samples such that a substantially similar expression profileor signature may be used to validate a finding of COPD disease state ormay be compared to the expression profile or signature from respiratorytract epithelium of subjects with normal lung tissue.

Expression profiles or signatures from diagnostic samples may benormalized to one or more house keeping gene transcripts such thatnormalized over and/or under expression of one or more of the genetranscripts in a respiratory tract epithelium sample may be indicativeof a COPD disease state.

D. COPD Classification Library

The COPD Classification Library in accordance with the presentdisclosure comprises at least one gene transcript whose relative and/ornormalized expression is indicative of a COPD disease state or theabsence of a COPD disease state. Gene transcripts which showdifferential expression in respiratory tract epithelium of subjects withCOPD diseased lung tissue include (i) transcripts comprising thesequences as set forth in SEQ ID NOS: 1 to 98, (ii) transcriptscomprising a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS: 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii). In some embodiments of thedisclosure, the library comprises at least one of the gene transcripts,each of the transcripts comprising a sequence as set forth in any one ofSEQ ID NOS: 1 to 98.

In some embodiments, the library comprises at least one transcript that(i) comprises a sequence as set forth in SEQ ID NOS: 1 to 98, (ii)comprises a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS: 1 to 98, or (iii) comprises a sequencewith substantial homology to (i) or (ii). In some embodiments, thelibrary comprises at least five transcripts, each of which (i) comprisesa sequence as set forth in SEQ ID NOS: 1 to 98, (ii) comprises afragment of at least 100 nucleotides of a sequence as set forth in anyone of SEQ ID NOS: 1 to 98, or (iii) comprises a sequence withsubstantial homology to (i) or (ii). In some embodiments, the librarycomprises at least 10 transcripts, each of which (i) comprises asequence as set forth in SEQ ID NOS: 1 to 98, (ii) comprises a fragmentof at least 100 nucleotides of a sequence as set forth in any one of SEQID NOS: 1 to 98, or (iii) comprises a sequence with substantial homologyto (i) or (ii). In some embodiments, the library comprises at least 15transcripts, each of which (i) comprises a sequence as set forth in SEQID NOS: 1 to 98, (ii) comprises a fragment of at least 100 nucleotidesof a sequence as set forth in any one of SEQ ID NOS: 1 to 98, or (iii)comprises a sequence with substantial homology to (i) or (ii). In someembodiments, the library comprises at least 20, at least 25, at least30, at least 35, at least 40, at least 45, at least 50, at least 55, atleast 60, at least 65, at least 70, at least 75, at least 80, at least85, at least 90, at lease 95 or at least 98 transcripts, each of the atleast 20, at least 25, at least 30, at least 35, at least 40, at least45, at least 50, at least 55, at least 60, at least 65, at least 70, atleast 75, at least 80, at least 85, at least 90, at lease 95 or at least98 transcripts each of which (i) comprises a sequence as set forth inSEQ ID NOS: 1 to 98, (ii) comprises a fragment of at least 100nucleotides of a sequence as set forth in any one of SEQ ID NOS: 1 to98, or (iii) comprises a sequence with substantial homology to (i) or(ii).

In some embodiments the library comprises transcripts that correspond tothe gene sequences listed in a table selected from Tables B, C, D, E, F,and G.

This disclosure also contemplates that alternative libraries may bedesigned that include in addition to transcripts comprising a sequenceas set forth in any one of SEQ ID NOs: 1 to 98, additional genetranscripts that are identified as having differential expression in therespiratory tract epithelium of subjects having COPD diseased lungtissue as compared to the respiratory tract epithelium of subjectshaving healthy lung tissue. As is known in the art, the publication andsequence databases can be mined using a variety of search strategies toidentify appropriate candidates for inclusion in the library. Forexample, currently available scientific and medical publicationdatabases such as Medline, Current Contents, OMIM (online Mendelianinheritance in man), various Biological and Chemical Abstracts, Journalindexes, and the like can be searched using term or key-word searches,or by author, title, or other relevant search parameters. Many suchdatabases are publicly available, and strategies and procedures foridentifying publications and their contents, for example, genes, othernucleotide sequences, descriptions, indications, expression pattern,etc, are well known to those skilled in the art. Numerous databases areavailable through the Internet for free or by subscription, see, forexample, the National Center Biotechnology Information (NCBI),Infotrieve, Thomson ISI, and Science Magazine (published by the AAAS)websites. Additional or alternative publication or citation databasesare also available that provide identical or similar types ofinformation, any of which can be employed in the context of thedisclosure. These databases can be searched for publications describingaltered gene expression between the respiratory tract epithelium ofsubjects having COPD diseased lung tissue as compared to the respiratorytract epithelium of subjects having healthy lung tissue. Additionalpotential candidate genes may be identified by searching the abovedescribed databases for differentially expressed proteins and byidentifying the nucleotide sequence encoding the differentiallyexpressed proteins.

In alternative embodiments the COPD Classification Library in accordancewith the present disclosure comprises at least one protein encoded by atranscript whose relative and/or normalized expression is indicative ofa COPD disease state or the absence of a COPD disease state. Genetranscripts which show differential expression in respiratory tractepithelium of subjects with COPD diseased lung tissue include (i)transcripts comprising the sequences as set forth in SEQ ID NOS: 1 to98, (ii) transcripts comprising a fragment of at least 100 nucleotidesof a sequence as set forth in any one of SEQ ID NOS: 1 to 98, or (iii) asequence with substantial homology to (i) or (ii). Thus, in someembodiments of the disclosure, the library comprises at least oneprotein encoded by at least one of SEQ ID NOS: 1 to 98. In someembodiments the at least one protein comprises a sequence selected fromSEQ ID NOS: 99-195.

E. COPD Classification Sets

A COPD Classification Set comprises one or more target sequencesidentified within each of the gene transcripts in the COPDclassification library, or a subset of these gene transcripts. Thetarget sequences may be within the coding and/or non-coding regions ofthe gene transcripts. The set can comprise one or a plurality of targetsequences from each gene transcript in the library, or subset thereof.The relative and/or normalized level of these target sequences in asample is indicative of the level of expression of the particular genetranscript and thus of having COPD diseased lung tissue or havinghealthy lung tissue. For example, the relative and/or normalizedexpression level of one or more of the target sequences may beindicative of a COPD disease state while the relative and/or normalizedexpression level of one or more other target sequences may be indicativeof healthy lung tissue.

Accordingly, in some embodiments the present disclosure provides for alibrary or catalog of candidate target sequences derived from thetranscripts (both coding and non-coding regions) of at least one genesuitable for classifying a COPD disease state as being present orabsent. In further embodiments, the library or catalog of candidatetarget sequences comprises target sequences as set forth in SEQ ID NOS:1 to 98. The library or catalog in effect provides a resource list oftranscripts from which target sequences appropriate for inclusion in aCOPD classification set can be derived. In one embodiment, an individualCOPD classification set may comprise target sequences derived from thetranscripts of one or more genes exhibiting a positive correlation witha COPD disease state. In some embodiments, an individual COPDclassification set may comprise target sequences derived from thetranscripts of one or more genes exhibiting a negative correlation witha COPD disease state. In some embodiments, an individual COPDClassification Set may comprise target sequences derived from thetranscripts of from two or more genes, wherein at least one gene has atranscript that exhibits a positive correlation with COPD and at leastone gene has a transcript that exhibits a negative correlation withCOPD.

In some embodiments, the COPD Classification Set comprises targetsequences derived from the transcripts of at least one gene. In someembodiments, the COPD Classification set comprises target sequencesderived from the transcripts of at least 5 genes. In some embodiments,the COPD Classification set comprises target sequences derived from thetranscripts of at least 10 genes. In some embodiments, the COPDClassification set comprises target sequences derived from thetranscripts of at least 15 genes. In some embodiments, the COPDClassification set comprises target sequences derived from thetranscripts of at least 20, at least 25, at least 30, at least 35, atleast 40, at least 45, at least 50, at least 55, at least 60, at least65, at least 70, at least 75, at least 80, at least 85, at least 90, atleast 95, or at least 98 genes.

Following the identification of candidate gene transcripts, appropriatetarget sequences can be identified by screening for target sequencesthat have been annotated to be associated with each specific gene locusfrom a number of annotation sources including GenBank, RefSeq, Ensembl,dbEST, GENSCAN, TWINSCAN, Exoniphy, Vega, microRNAs registry and others(see Affymetrix Exon Array design note).

As part of the target sequence selection process, target sequences canbe further evaluated for potential cross-hybridization against otherputative transcribed sequences in the design (but not the entire genome)to identify only those target sequences that are predicted to uniquelyhybridize to a single target.

The set of target sequences that are predicted to uniquely hybridize toa single target can be further filtered using a variety of criteriaincluding, for example, sequence length, for their mean expressionlevels across a wide selection of human tissues, as being representativeof transcripts expressed either as novel alternative (i.e.,non-consensus) exons, alternative retained introns, novel exons 5′ or 3′of the gene's transcriptional start site or representing transcriptsexpressed in a manner antisense to the gene, and others.

In some embodiments, the COPD Classification Set comprises targetsequences derived from the sequences as set forth in at least onesequence selected from SEQ ID NOs: 1-98.

In some embodiments, the COPD Classification Set comprises at least onetarget sequences derived from each of the sequences set forth in SEQ IDNOs: 1-98.

In some embodiments, the potential set of target sequences can befiltered for their expression levels using the multi-tissue expressiondata made publicly available by Affymetrix at(http://www.affymetrix.com/support/technical/sample data/exon arraydata.affx) such that probes with, for example, expression acrossnumerous tissues or no expression in respiratory tract epithelium can beexcluded.

In some embodiments, the COPD classification set can be specificallydesigned to be indicative of COPD disease in general or alternatively beindicative of one or more individual clinical manifestations of COPD.

E. Validation of Target Sequences

Following selection in silico or otherwise of target sequences, eachtarget sequence suitable for use in the COPD classification set may bevalidated to confirm differential relative or normalized expression inrespiratory tract epithelium of subjects having COPD and/or not havingCOPD. Validation methods are known in the art and include hybridizationtechniques such as microarray analysis or Northern blotting usingappropriate controls, and may include one or more additional steps, suchas reverse transcription, transcription, PCR, RT-PCR and the like. Thevalidation of the target sequences using these methods is well withinthe abilities of a worker skilled in the art.

F. Minimal Expression Signature

In some embodiments, individual COPD classification sets provide for atleast a determination of a minimal expression signature, capable ofdistinguishing between the presence of COPD in lung tissue. Means fordetermining the appropriate number of target sequences necessary toobtain a minimal expression signature are known in the art and include,without limitation, the Nearest Shrunken Centroids (NSC) method.

In the NSC method (see US 20070031873), a standardized centroid iscomputed for each class. This is the average gene expression for eachgene in each class divided by the within-class standard deviation forthat gene. Nearest centroid classification takes the gene expressionprofile of a new sample, and compares it to each of these classcentroids. The class whose centroid that it is closest to, in squareddistance, is the predicted class for that new sample. Nearest shrunkencentroid classification “shrinks” each of the class centroids toward theoverall centroid for all classes by an amount called the threshold. Thisshrinkage consists of moving the centroid towards zero by threshold,setting it equal to zero if it hits zero. For example if threshold was2.0, a centroid of 3.2 would be shrunk to 1.2, a centroid of −3.4 wouldbe shrunk to −1.4, and a centroid of 1.2 would be shrunk to zero. Aftershrinking the centroids, the new sample is classified by the usualnearest centroid rule, but using the shrunken class centroids. Thisshrinkage can make the classifier more accurate by reducing the effectof noisy genes and provides an automatic gene selection. In particular,if a gene is shrunk to zero for all classes, then it is eliminated fromthe prediction rule. Alternatively, it may be set to zero for allclasses except one, and it can be learned that the high or lowexpression for that gene characterizes that class. The user decides onthe value to use for threshold. Typically one examines a number ofdifferent choices. To guide in this choice, PAM does K-foldcross-validation for a range of threshold values. The samples aredivided up at random into K roughly equally sized parts. For each partin turn, the classifier is built on the other K-1 parts then tested onthe remaining part. This is done for a range of threshold values, andthe cross-validated misclassification error rate is reported for eachthreshold value. Typically, the user would choose the threshold valuegiving the minimum cross-validated misclassification error rate.

Alternatively, minimal expression signatures can be established throughthe use of optimization algorithms such as the mean variance algorithmwidely used in establishing stock portfolios. This method is describedin detail in US patent publication number 20030194734. Essentially, themethod calls for the establishment of a set of inputs (stocks infinancial applications, expression as measured by intensity here) thatwill optimize the return (e.g., signal that is generated) one receivesfor using it while minimizing the variability of the return. In otherwords, the method calls for the establishment of a set of inputs (e.g.,expression as measured by intensity) that will optimize the signal whileminimizing variability. Many commercial software programs are availableto conduct such operations. “Wagner Associates Mean-VarianceOptimization Application,” referred to as “Wagner Software” throughoutthis specification, is one suitable option. This software uses functionsfrom the “Wagner Associates Mean-Variance Optimization Library” todetermine an efficient frontier and optimal portfolios in the Markowitzsense. Use of this type of software requires that microarray data betransformed so that it can be treated as an input in the way stockreturn and risk measurements are used when the software is used for itsintended financial analysis purposes.

The process of selecting a minimal expression signature can also includethe application of heuristic rules. Preferably, such rules areformulated based on biology and an understanding of the technology usedto produce clinical results. More preferably, they are applied to outputfrom the optimization method. For example, the mean variance method ofportfolio selection can be applied to microarray data for a number ofgenes differentially expressed in the respiratory tract epithelium ofsubjects with COPD.

Other heuristic rules can be applied that are not necessarily related tothe biology in question. For example, one can apply a rule that only aprescribed percentage of the portfolio can be represented by aparticular gene or group of genes. Commercially available software suchas the Wagner Software readily accommodates these types of heuristics.This can be useful, for example, when factors other than accuracy andprecision have an impact on the desirability of including one or moregenes.

In some embodiments, the COPD classification set for obtaining a minimalexpression signature comprises at least one, two, three, four, five,six, eight, 10, 15, 20, 25 or more of target sequences shown to have apositive correlation with COPD disease state, for example those depictedin SEQ ID NOs: 1-98 or a subset thereof.

In some embodiments, the COPD classification set comprises targetsequences for detecting expression products of SEQ ID NOs:1-98. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table B. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table C. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table D. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table E. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table F. In someembodiments the COPD classification set comprises target sequences fordetecting expression products of each gene listed in Table G.

The COPD classification set can optionally include one or more targetsequences specifically derived from the transcripts of one or morehousekeeping genes and/or one or more internal control target sequencesand/or one or more negative control target sequences. In one embodiment,these target sequences can, for example, be used to normalize expressiondata. Housekeeping genes from which target sequences for inclusion in aCOPD Classification Set can be derived from are known in the art andinclude those genes in which are expressed at a constant level in normalrespiratory tract epithelium.

The target sequences described herein may be used alone or incombination with each other or with other known or later identifieddisease markers.

G. COPD Classification Probes/Primers

The systems of this disclosure provide combinations of polynucleotideprobes that are capable of detecting the target sequences of the COPDClassification Sets. Individual polynucleotide probes comprise anucleotide sequence derived from the nucleotide sequence of the targetsequences or complementary sequences thereof. The nucleotide sequence ofthe polynucleotide probe is such that it corresponds to, or iscomplementary to the target sequences. The polynucleotide probe canspecifically hybridize under either stringent or lowered stringencyhybridization conditions to a region of the target sequences, to thecomplement thereof, or to a nucleic acid sequence (such as a cDNA)derived therefrom.

The selection of the polynucleotide probe sequences and determination oftheir uniqueness may be carried out in silico using techniques known inthe art, for example, based on a BLASTN search of the polynucleotidesequence in question against gene sequence databases, such as the HumanGenome Sequence, UniGene, dbEST or the non-redundant database at NCBI.In some embodiments of the disclosure, the polynucleotide probe iscomplementary to a region of a target mRNA derived from a PSR in theCOPD classification set. Computer programs can also be employed toselect probe sequences that will not cross hybridize or will nothybridize non-specifically.

One skilled in the art will understand that the nucleotide sequence ofthe polynucleotide probe need not be identical to its target sequence inorder to specifically hybridise thereto. The polynucleotide probes ofthe present disclosure, therefore, comprise a nucleotide sequence thatis at least about 75% identical to a region of the target gene or mRNA.In some embodiments, the nucleotide sequence of the polynucleotide probeis at least about 90% identical a region of the target gene or mRNA. Insome embodiments, the nucleotide sequence of the polynucleotide probe isat least about 95% identical to a region of the target gene or mRNA.Methods of determining sequence identity are known in the art and can bedetermined, for example, by using the BLASTN program of the Universityof Wisconsin Computer Group (GCG) software or provided on the NCBIwebsite. The nucleotide sequence of the polynucleotide probes of thepresent invention may exhibit variability by differing (e.g. bynucleotide substitution, including transition or transversion) at one,two, three, four or more nucleotides from the sequence of the targetgene.

Other criteria known in the art may be employed in the design of thepolynucleotide probes of the present disclosure. For example, the probescan be designed to have <50% G content and/or between about 25% andabout 70% G+C content. Strategies to optimize probe hybridization to thetarget nucleic acid sequence can also be included in the process ofprobe selection. Hybridization under particular pH, salt, andtemperature conditions can be optimized by taking into account meltingtemperatures and by using empirical rules that correlate with desiredhybridization behaviours. Computer models may be used for predicting theintensity and concentration-dependence of probe hybridization.

As is known in the art, in order to represent a unique sequence in thehuman genome, a probe should be at least about 15 nucleotides in length.Accordingly, the polynucleotide probes of the present invention range inlength from about 15 nucleotides to the full length of the PSR or targetmRNA. In some embodiments, the polynucleotide probes are at least about15 nucleotides in length. In some embodiments, the polynucleotide probesare at least about 20 nucleotides in length. In some embodiments, thepolynucleotide probes are at least about 25 nucleotides in length. Insome embodiments, the polynucleotide probes are between about 15nucleotides and about 500 nucleotides in length. In some embodiments,the polynucleotide probes are between about 15 nucleotides and about 450nucleotides, about 15 nucleotides and about 400 nucleotides, about 15nucleotides and about 350 nucleotides, about 15 nucleotides and about300 nucleotides, about 15 nucleotides and about 250 nucleotides, about15 nucleotides and about 200 nucleotides, about 15 nucleotides and about150 nucleotides, about 15 nucleotides and about 100 nucleotides, about15 nucleotides and about 50 nucleotides in length.

The polynucleotide probes of a COPD classification set can comprise RNA,DNA, RNA or DNA mimetics, or combinations thereof, and can besingle-stranded or double-stranded. Thus the polynucleotide probes canbe composed of naturally-occurring nucleobases, sugars and covalentinternucleoside (backbone) linkages as well as polynucleotide probeshaving non-naturally-occurring portions which function similarly. Suchmodified or substituted polynucleotide probes may provide desirableproperties such as, for example, enhanced affinity for a target gene andincreased stability.

The system of the present invention further provides for primers andprimer pairs capable of amplifying target sequences defined by the COPDclassification set, or fragments or subsequences or complements thereof.The nucleotide sequences of the COPD classifying set may be provided incomputer-readable media for in silico applications and as a basis forthe design of appropriate primers for amplification of one or moretarget sequences of the COPD classifying set.

Primers based on the nucleotide sequences of target sequences can bedesigned for use in amplification of the target sequences. For use inamplification reactions such as PCR, a pair of primers will be used. Theexact composition of the primer sequences is not critical, but for mostapplications the primers will hybridize to specific sequences of theCOPD classification set under stringent conditions, particularly underconditions of high stringency, as known in the art. The pairs of primersare usually chosen so as to generate an amplification product of atleast about 50 to about 100 nucleotides. Algorithms for the selection ofprimer sequences are generally known, and are available in commercialsoftware packages. These primers may be used in standard quantitative orqualitative PCR-based assays to assess transcript expression levels ofRNAs defined by the COPD classification set. Alternatively, theseprimers may be used in combination with probes, such as molecularbeacons in amplifications using real-time PCR.

In some embodiments, the primers or primer pairs, when used in anamplification reaction, specifically amplify at least a portion of anucleic acid depicted in one of SEQ ID NOs: 1-98, an RNA form thereof,or a complement to either thereof. Optionally, when amplified, eitherstand produced by amplification may be provided in purified and/orisolated form.

As is known in the art, a nucleoside is a base-sugar combination and anucleotide is a nucleoside that further includes a phosphate groupcovalently linked to the sugar portion of the nucleoside. In formingoligonucleotides, the phosphate groups covalently link adjacentnucleosides to one another to form a linear polymeric compound, with thenormal linkage or backbone of RNA and DNA being a 3′ to 5′phosphodiester linkage. Specific examples of polynucleotide probes orprimers useful in this invention include oligonucleotides containingmodified backbones or non-natural internucleoside linkages. As definedin this specification, oligonucleotides having modified backbonesinclude both those that retain a phosphorus atom in the backbone andthose that lack a phosphorus atom in the backbone. For the purposes ofthe present invention, and as sometimes referenced in the art, modifiedoligonucleotides that do not have a phosphorus atom in theirinternucleoside backbone can also be considered to be oligonucleotides.

Exemplary polynucleotide probes or primers having modifiedoligonucleotide backbones include, for example, those with one or moremodified internucleoside linkages that are phosphorothioates, chiralphosphorothioates, phosphorodithioates, phosphotriesters,aminoalkylphosphotriesters, methyl and other alkyl phosphonatesincluding 3′-alkylene phosphonates and chiral phosphonates,phosphinates, phosphoramidates including 3′ amino phosphoramidate andaminoalkylphosphoramidates, thionophosphoramidates,thionoalkylphosphonates, thionoalkylphosphotriesters, andboranophosphates having normal 3′-5′ linkages, 2′-5′ linked analogs ofthese, and those having inverted polarity wherein the adjacent pairs ofnucleoside units are linked 3′-5′ to 5′-3′ or 2′-5′ to 5′-2′. Varioussalts, mixed salts and free acid forms are also included.

Exemplary modified oligonucleotide backbones that do not include aphosphorus atom are formed by short chain alkyl or cycloalkylinternucleoside linkages, mixed heteroatom and alkyl or cycloalkylinternucleoside linkages, or one or more short chain heteroatomic orheterocyclic internucleoside linkages. Such backbones include morpholinolinkages (formed in part from the sugar portion of a nucleoside);siloxane backbones; sulfide, sulfoxide and sulphone backbones;formacetyl and thioformacetyl backbones; methylene formacetyl andthioformacetyl backbones; alkene containing backbones; sulphamatebackbones; methyleneimino and methylenehydrazino backbones; sulphonateand sulfonamide backbones; amide backbones; and others having mixed N,O, S and CH₂ component parts.

The present disclosure also contemplates oligonucleotide mimetics inwhich both the sugar and the internucleoside linkage of the nucleotideunits are replaced with novel groups. The base units are maintained forhybridization with an appropriate nucleic acid target compound. Anexample of such an oligonucleotide mimetic, which has been shown to haveexcellent hybridization properties, is a peptide nucleic acid (PNA)[Nielsen et al., Science, 254:1497-1500 (1991)]. In PNA compounds, thesugar-backbone of an oligonucleotide is replaced with an amidecontaining backbone, in particular an aminoethylglycine backbone. Thenucleobases are retained and are bound directly or indirectly toaza-nitrogen atoms of the amide portion of the backbone.

The present disclosure also contemplates polynucleotide probes orprimers comprising “locked nucleic acids” (LNAs), which are novelconformationally restricted oligonucleotide analogues containing amethylene bridge that connects the 2′-O of ribose with the 4′-C (see,Singh et al., Chem. Commun., 1998, 4:455-456). LNA and LNA analoguesdisplay very high duplex thermal stabilities with complementary DNA andRNA, stability towards 3′-exonuclease degradation, and good solubilityproperties. Synthesis of the LNA analogues of adenine, cytosine,guanine, 5-methylcytosine, thymine and uracil, their oligomerization,and nucleic acid recognition properties have been described (see Koshkinet al., Tetrahedron, 1998, 54:3607-3630). Studies of mis-matchedsequences show that LNA obey the Watson-Crick base pairing rules withgenerally improved selectivity compared to the corresponding unmodifiedreference strands.

LNAs form duplexes with complementary DNA or RNA or with complementaryLNA, with high thermal affinities. The universality of LNA-mediatedhybridization has been emphasized by the formation of exceedingly stableLNA:LNA duplexes (Koshkin et al., J. Am. Chem. Soc., 1998,120:13252-13253). LNA:LNA hybridization was shown to be the mostthermally stable nucleic acid type duplex system, and the RNA-mimickingcharacter of LNA was established at the duplex level. Introduction ofthree LNA monomers (T or A) resulted in significantly increased meltingpoints toward DNA complements.

Synthesis of 2′-amino-LNA (Singh et al., J. Org. Chem., 1998, 63,10035-10039) and 2′-methylamino-LNA has been described and thermalstability of their duplexes with complementary RNA and DNA strandsreported. Preparation of phosphorothioate-LNA and 2′-thio-LNA have alsobeen described (Kumar et al., Bioorg. Med. Chem. Lett., 1998,8:2219-2222).

Modified polynucleotide probes or primers may also contain one or moresubstituted sugar moieties. For example, oligonucleotides may comprisesugars with one of the following substituents at the 2′ position: OH; F;O-, S-, or N-alkyl; O-, S-, or N-alkenyl; O-, S- or N-alkynyl; orO-alkyl-O-alkyl, wherein the alkyl, alkenyl and alkynyl may besubstituted or unsubstituted C₁ to C₁₀ alkyl or C₂ to C₁₀ alkenyl andalkynyl. Examples of such groups are: O[(CH₂)_(n)O]_(m)CH₃,O(CH₂)_(n)OCH₃, O(CH₂)_(n)NH₂, (CH₂)_(n)CH₃, O(CH₂)_(n)ONH₂, andO(CH₂)_(n)ON[(CH₂)_(n)CH₃)]₂, where n and m are from 1 to about 10.Alternatively, the oligonucleotides may comprise one of the followingsubstituents at the 2′ position: C.sub.₁ to C.sub.₁₀ lower alkyl,substituted lower alkyl, alkaryl, aralkyl, O-alkaryl or O-aralkyl, SH,SCH₃, OCN, Cl, Br, CN, CF₃, OCF₃, SOCH₃, SO₂CH₃, ONO₂, NO₂, N₃, NH₂,heterocycloalkyl, heterocycloalkaryl, aminoalkylamino, polyalkylamino,substituted silyl, an RNA cleaving group, a reporter group, anintercalator, a group for improving the pharmacokinetic properties of anoligonucleotide, or a group for improving the pharmacodynamic propertiesof an oligonucleotide, and other substituents having similar properties.Specific examples include 2′-methoxyethoxy (2′-O—CH₂CH₂OCH₃, also knownas 2′-O-(2-methoxyethyl) or 2′-MOE) [Martin et al., Helv. Chim. Acta,78:486-504 (1995)], 2′-dimethylaminooxyethoxy (O(CH₂)₂ON(CH₃)₂ group,also known as 2′-DMAOE), 2′-methoxy (2′-O—CH3), 2′-aminopropoxy(2′-OCH₂CH₂CH₂NH₂) and 2′-fluoro (2′-F).

Similar modifications may also be made at other positions on thepolynucleotide probes or primers, particularly the 3′ position of thesugar on the 3′ terminal nucleotide or in 2′-5′ linked oligonucleotidesand the 5′ position of 5′ terminal nucleotide. Polynucleotide probes orprimers may also have sugar mimetics such as cyclobutyl moieties inplace of the pentofuranosyl sugar.

Polynucleotide probes or primers may also include modifications orsubstitutions to the nucleobase. As used herein, “unmodified” or“natural” nucleobases include the purine bases adenine (A) and guanine(G), and the pyrimidine bases thymine (T), cytosine (C) and uracil (U).Modified nucleobases include other synthetic and natural nucleobasessuch as 5-methylcytosine (5-me-C), 5-hydroxymethyl cytosine, xanthine,hypoxanthine, 2-aminoadenine, 6-methyl and other alkyl derivatives ofadenine and guanine, 2-propyl and other alkyl derivatives of adenine andguanine, 2-thiouracil, 2-thiothymine and 2-thiocytosine, 5-halouraciland cytosine, 5-propynyl uracil and cytosine, 6-azo uracil, cytosine andthymine, 5-uracil (pseudouracil), 4-thiouracil, 8-halo, 8-amino,8-thiol, 8-thioalkyl, 8-hydroxyl and other 8-substituted adenines andguanines, 5-halo particularly 5-bromo, 5-trifluoromethyl and other5-substituted uracils and cytosines, 7-methylguanine and7-methyladenine, 8-azaguanine and 8-azaadenine, 7-deazaguanine and7-deazaadenine and 3-deazaguanine and 3-deazaadenine. Furthernucleobases include those disclosed in U.S. Pat. No. 3,687,808; TheConcise Encyclopedia Of Polymer Science And Engineering, (1990) pp858-859, Kroschwitz, J. I., ed. John Wiley & Sons; Englisch et al.,Angewandte Chemie, Int. Ed., 30:613 (1991); and Sanghvi, Y. S., (1993)Antisense Research and Applications, pp 289-302, Crooke, S. T. andLebleu, B., ed., CRC Press. Certain of these nucleobases areparticularly useful for increasing the binding affinity of thepolynucleotide probes of the invention. These include 5-substitutedpyrimidines, 6-azapyrimidines and N-2, N-6 and O-6 substituted purines,including 2-aminopropyladenine, 5-propynyluracil and 5-propynylcytosine.5-methylcytosine substitutions have been shown to increase nucleic acidduplex stability by 0.6-1.2° C. [Sanghvi, Y. S., (1993) AntisenseResearch and Applications, pp 276-278, Crooke, S. T. and Lebleu, B.,ed., CRC Press, Boca Raton].

One skilled in the art will recognize that it is not necessary for allpositions in a given polynucleotide probe or primer to be uniformlymodified. The present disclosure, therefore, contemplates theincorporation of more than one of the aforementioned modifications intoa single polynucleotide probe or even at a single nucleoside within theprobe or primer.

One skilled in the art will also appreciate that the nucleotide sequenceof the entire length of the polynucleotide probe or primer does not needto be derived from the target sequence. Thus, for example, thepolynucleotide probe may comprise nucleotide sequences at the 5′ and/or3′ to the transcription start and stop sites, respectively that are notderived from the target sequences. Nucleotide sequences which are notderived from the nucleotide sequence of the target sequence may provideadditional functionality to the polynucleotide probe. For example, theymay provide a restriction enzyme recognition sequence or a “tag” thatfacilitates detection, isolation, purification or immobilisation onto asolid support. Alternatively, the additional nucleotides may provide aself-complementary sequence that allows the primer/probe to adopt ahairpin configuration. Such configurations are necessary for certainprobes, for example, molecular beacon and Scorpion probes, which can beused in solution hybridization techniques.

The polynucleotide probes or primers can incorporate moieties useful indetection, isolation, purification, or immobilisation, if desired. Suchmoieties are well-known in the art (see, for example, Ausubel et al.,(1997 & updates) Current Protocols in Molecular Biology, Wiley & Sons,New York) and are chosen such that the ability of the probe to hybridizewith its target sequence is not affected.

Examples of suitable moieties are detectable labels, such asradioisotopes, fluorophores, chemiluminophores, enzymes, colloidalparticles, and fluorescent microparticles, as well as antigens,antibodies, haptens, avidin/streptavidin, biotin, haptens, enzymecofactors/substrates, enzymes, and the like.

A label can optionally be attached to or incorporated into a probe orprimer polynucleotide to allow detection and/or quantitation of a targetpolynucleotide representing the target sequence of interest. The targetpolynucleotide may be the expressed target sequence RNA itself, a cDNAcopy thereof, or an amplification product derived therefrom, and may bethe positive or negative strand, so long as it can be specificallydetected in the assay being used. Similarly, an antibody may be labeled.

In certain multiplex formats, labels used for detecting differenttargets may be distinguishable. The label can be attached directly(e.g., via covalent linkage) or indirectly, e.g., via a bridgingmolecule or series of molecules (e.g., a molecule or complex that canbind to an assay component, or via members of a binding pair that can beincorporated into assay components, e.g. biotin-avidin or streptavidin).Many labels are commercially available in activated forms which canreadily be used for such conjugation (for example through amineacylation), or labels may be attached through known or determinableconjugation schemes, many of which are known in the art.

Labels useful in the disclosure include any substance which can bedetected when bound to or incorporated into the biomolecule of interest.Any effective detection method can be used, including optical,spectroscopic, electrical, piezoelectrical, magnetic, Raman scattering,surface plasmon resonance, colorimetric, calorimetric, etc. A label istypically selected from a chromophore, a lumiphore, a fluorophore, onemember of a quenching system, a chromogen, a hapten, an antigen, amagnetic particle, a material exhibiting nonlinear optics, asemiconductor nanocrystal, a metal nanoparticle, an enzyme, an antibodyor binding portion or equivalent thereof, an aptamer, and one member ofa binding pair, and combinations thereof. Quenching schemes may be used,wherein a quencher and a fluorophore as members of a quenching pair maybe used on a probe, such that a change in optical parameters occurs uponbinding to the target introduce or quench the signal from thefluorophore. One example of such a system is a molecular beacon.Suitable quencher/fluorophore systems are known in the art. The labelmay be bound through a variety of intermediate linkages. For example, apolynucleotide may comprise a biotin-binding species, and an opticallydetectable label may be conjugated to biotin and then bound to thelabeled polynucleotide. Similarly, a polynucleotide sensor may comprisean immunological species such as an antibody or fragment, and asecondary antibody containing an optically detectable label may beadded.

Chromophores useful in the methods described herein include anysubstance which can absorb energy and emit light. For multiplexedassays, a plurality of different signaling chromophores can be used withdetectably different emission spectra. The chromophore can be alumophore or a fluorophore. Typical fluorophores include fluorescentdyes, semiconductor nanocrystals, lanthanide chelates,polynucleotide-specific dyes and green fluorescent protein.

Coding schemes may optionally be used, comprising encoded particlesand/or encoded tags associated with different polynucleotides of theinvention. A variety of different coding schemes are known in the art,including fluorophores, including SCNCs, deposited metals, and RF tags.

Polynucleotides from the described target sequences may be employed asprobes for detecting target sequences expression, for ligationamplification schemes, or may be used as primers for amplificationschemes of all or a portion of a target sequences. When amplified,either strand produced by amplification may be provided in purifiedand/or isolated form.

In some embodiments, polynucleotides of the disclosure include a nucleicacid depicted in (a) any of SEQ ID NOs: 1-98; (b) an RNA form of any ofthe nucleic acids depicted in SEQ ID NOs: 1-98; (c) a peptide nucleicacid form of any of the nucleic acids depicted in SEQ ID NOs: 1-98; (d)a nucleic acid comprising at least 20 consecutive bases of any of (a-c);(e) a nucleic acid comprising at least 25 consecutive bases having atleast 90% sequence identity to any of (a-c); and a complement to any of(a-e).

Complements may take any polymeric form capable of base pairing to thespecies recited in (a)-(e), including nucleic acid such as RNA or DNA,or may be a neutral polymer such as a peptide nucleic acid.Polynucleotides of the disclosure can be selected from the subsets ofthe recited nucleic acids described herein, as well as theircomplements.

In some embodiments, polynucleotides of the disclosure comprise at least20 consecutive bases as depicted in SEQ ID NOs:1-98, or a complementthereto. The polynucleotides may comprise at least 21, 22, 23, 24, 25,27, 30, 32, 35 or more consecutive bases as depicted in SEQ ID NOs:1-98.

The polynucleotides may be provided in a variety of formats, includingas solids, in solution, or in an array. The polynucleotides mayoptionally comprise one or more labels, which may be chemically and/orenzymatically incorporated into the polynucleotide.

In some embodiments, solutions comprising polynucleotide and a solventare also provided. In some embodiments, the solvent may be water or maybe predominantly aqueous. In some embodiments, the solution may compriseat least two, three, four, five, six, seven, eight, nine, ten, twelve,fifteen, seventeen, twenty or more different polynucleotides, includingprimers and primer pairs, of the invention. Additional substances may beincluded in the solution, alone or in combination, including one or morelabels, additional solvents, buffers, biomolecules, polynucleotides, andone or more enzymes useful for performing methods described herein,including polymerases and ligases. The solution may further comprise aprimer or primer pair capable of amplifying a polynucleotide of theinvention present in the solution.

In some embodiments, one or more polynucleotides provided herein can beprovided on a substrate. The substrate can comprise a wide range ofmaterial, either biological, nonbiological, organic, inorganic, or acombination of any of these. For example, the substrate may be apolymerized Langmuir Blodgett film, functionalized glass, Si, Ge, GaAs,GaP, SiO₂, SiN₄, modified silicon, or any one of a wide variety of gelsor polymers such as (poly)tetrafluoroethylene,(poly)vinylidenedifluoride, polystyrene, cross-linked polystyrene,polyacrylic, polylactic acid, polyglycolic acid, poly(lactidecoglycolide), polyanhydrides, poly(methyl methacrylate),poly(ethylene-co-vinyl acetate), polysiloxanes, polymeric silica,latexes, dextran polymers, epoxies, polycarbonates, or combinationsthereof. Conducting polymers and photoconductive materials can be used.

Substrates can be planar crystalline substrates such as silica basedsubstrates (e.g. glass, quartz, or the like), or crystalline substratesused in, e.g., the semiconductor and microprocessor industries, such assilicon, gallium arsenide, indium doped GaN and the like, and includessemiconductor nanocrystals.

The substrate can take the form of an array, a photodiode, anoptoelectronic sensor such as an optoelectronic semiconductor chip oroptoelectronic thin-film semiconductor, or a biochip. The location(s) ofprobe(s) on the substrate can be addressable; this can be done in highlydense formats, and the location(s) can be microaddressable ornanoaddressable.

Silica aerogels can also be used as substrates, and can be prepared bymethods known in the art. Aerogel substrates may be used as freestanding substrates or as a surface coating for another substratematerial.

The substrate can take any form and typically is a plate, slide, bead,pellet, disk, particle, microparticle, nanoparticle, strand,precipitate, optionally porous gel, sheets, tube, sphere, container,capillary, pad, slice, film, chip, multiwell plate or dish, opticalfiber, etc. The substrate can be any form that is rigid or semi-rigid.The substrate may contain raised or depressed regions on which an assaycomponent is located. The surface of the substrate can be etched usingknown techniques to provide for desired surface features, for exampletrenches, v-grooves, mesa structures, or the like.

Surfaces on the substrate can be composed of the same material as thesubstrate or can be made from a different material, and can be coupledto the substrate by chemical or physical means. Such coupled surfacesmay be composed of any of a wide variety of materials, for example,polymers, plastics, resins, polysaccharides, silica or silica-basedmaterials, carbon, metals, inorganic glasses, membranes, or any of theabove-listed substrate materials. The surface can be opticallytransparent and can have surface Si—OH functionalities, such as thosefound on silica surfaces.

The substrate and/or its optional surface can be chosen to provideappropriate characteristics for the synthetic and/or detection methodsused. The substrate and/or surface can be transparent to allow theexposure of the substrate by light applied from multiple directions. Thesubstrate and/or surface may be provided with reflective “mirror”structures to increase the recovery of light.

The substrate and/or its surface is generally resistant to, or istreated to resist, the conditions to which it is to be exposed in use,and can be optionally treated to remove any resistant material afterexposure to such conditions.

The substrate or a region thereof may be encoded so that the identity ofthe sensor located in the substrate or region being queried may bedetermined. Any suitable coding scheme can be used, for example opticalcodes, RFID tags, magnetic codes, physical codes, fluorescent codes, andcombinations of codes.

H. Preparation of Probes and Primers

The polynucleotide probes or primers of the present disclosure can beprepared by conventional techniques well-known to those skilled in theart. For example, the polynucleotide probes can be prepared usingsolid-phase synthesis using commercially available equipment. As iswell-known in the art, modified oligonucleotides can also be readilyprepared by similar methods. The polynucleotide probes can also besynthesized directly on a solid support according to methods standard inthe art. This method of synthesizing polynucleotides is particularlyuseful when the polynucleotide probes are part of a nucleic acid array.

Polynucleotide probes or primers can be fabricated on or attached to thesubstrate by any suitable method, for example the methods described inU.S. Pat. No. 5,143,854, PCT Publ. No. WO 92/10092, U.S. patentapplication Ser. No. 07/624,120, filed Dec. 6, 1990 (now abandoned),Fodor et al., Science, 251: 767-777 (1991), and PCT Publ. No. WO90/15070). Techniques for the synthesis of these arrays using mechanicalsynthesis strategies are described in, e.g., PCT Publication No. WO93/09668 and U.S. Pat. No. 5,384,261. Still further techniques includebead based techniques such as those described in PCT Appl. No.PCT/US93/04145 and pin based methods such as those described in U.S.Pat. No. 5,288,514. Additional flow channel or spotting methodsapplicable to attachment of sensor polynucleotides to a substrate aredescribed in U.S. patent application Ser. No. 07/980,523, filed Nov. 20,1992, and U.S. Pat. No. 5,384,261.

Alternatively, the polynucleotide probes of the present disclosure canbe prepared by enzymatic digestion of the naturally occurring targetgene, or mRNA or cDNA derived therefrom, by methods known in the art.

I. COPD Classification Methods

As demonstrated in the Examples, the inventors have made the surprisingdiscovery that the expression of gene sets in the airway epithelium of asubject reflects the COPD disease status of the subject. That findingtogether with the identification of 98 different genes that aredifferentially expressed in the respiratory tract epithelium of subjectswith COPD compared to normal control subjects has allowed the inventorsto provide in this disclosure methods of classifying the COPD diseasestatus of a subject.

Accordingly, this disclosure provides methods for classifying thechronic obstructive pulmonary disease (COPD) status of a subject. Themethods comprise providing a tissue sample obtained from the respiratorytract epithelium of the subject. The methods further include determiningthe expression level of at least one transcript comprising (i) asequence as set forth in any one of SEQ ID NOS. 1 to 98, (ii) a fragmentof at least 100 nucleotides of a sequence as set forth in any one of SEQID NOS. 1 to 98, or (iii) a sequence with substantial homology to (i) or(ii), in the tissue sample to provide an expression pattern profile. Themethods may further include comparing the expression pattern profilewith a reference expression pattern profile. The methods may furtherinclude classifying the COPD status of the subject based on thecomparing.

The methods use the COPD classification sets, probes and primersdescribed herein to provide expression signatures or profiles from atest sample derived from the respiratory tract epithelium of a subjecthaving or suspected of having COPD and/or undergoing a therapeuticintervention comprising administering an anti-COPD therapeutic agent. Insome embodiments, such methods involve contacting the test sample withCOPD classifying probes (either in solution or immobilized) underconditions that permit hybridization of the probe(s) to any targetnucleic acid(s) present in the test sample and then detecting anyprobe:target duplexes formed as an indication of the presence of thetarget nucleic acid in the sample. Expression patterns thus determinedare then compared to one or more reference profiles or signatures.Optionally, the expression pattern can be normalized. The methods usethe COPD classification sets, probes and primers described herein toprovide expression signatures or profiles from a test sample derivedfrom a subject to classify the COPD disease status of the subject.

The assay/method is capable in some embodiments of discriminating COPDdisease status with good accuracy even without the need for a biopsie oflung tissue from the subject.

In some embodiments, such methods involve the specific amplification oftarget sequences nucleic acid(s) present in the test sample usingmethods known in the art to generate an expression profile or signaturewhich is then compared to a reference profile or signature.

In some embodiments, the disclosure further provides for diagnosingCOPD, for prognosing patient outcome, and/or for designating treatmentmodalities.

In some embodiments, the methods generate expression profiles orsignatures detailing the expression of at least 2, at least 3, at least4, at least 5, at least 10, at least 15, at least 20, at least 25, atleast 30, at least 35, at least 40, at least 45, at least 50, at least55, at least 65, at least 70, at least 75, at least 80, at least 85, atleast 90, at least 95 or all 98 target sequences having altered relativeexpression in COPD disclosed herein. In some embodiments the methodsgenerate expression profiles or signatures detailing the expression ofeach gene listed in Table B. In some embodiments the methods generateexpression profiles or signatures detailing the expression of each genelisted in Table C. In some embodiments the methods generate expressionprofiles or signatures detailing the expression of each gene listed inTable D. In some embodiments the methods generate expression profiles orsignatures detailing the expression of each gene listed in Table E. Insome embodiments the methods generate expression profiles or signaturesdetailing the expression of each gene listed in Table F. In someembodiments the methods generate expression profiles or signaturesdetailing the expression of each gene listed in Table G.

In some embodiments, the methods detect combinations of expressionlevels of sequences exhibiting positive correlation with a diseasestatus. In some embodiments, the methods detect a minimal expressionsignature.

Any method of detecting and/or quantitating the expression of theencoded target sequences can in principle be used in the methods ofclassifying the COPD disease status of a subject. Such methods caninclude Northern blotting, array or microarray hybridization, byenzymatic cleavage of specific structures (e.g., an Invader® assay,Third Wave Technologies, e.g. as described in U.S. Pat. Nos. 5,846,717,6,090,543; 6,001,567; 5,985,557; and 5,994,069) and amplificationmethods, e.g. RT-PCR, including in a TaqMan® assay (PE Biosystems,Foster City, Calif., e.g. as described in U.S. Pat. Nos. 5,962,233 and5,538,848), and may be quantitative or semi-quantitative, and may varydepending on the origin, amount and condition of the availablebiological sample. Combinations of these methods may also be used. Forexample, nucleic acids may be amplified, labeled and subjected tomicroarray analysis. Single-molecule sequencing (e.g., Illumina,Helicos, PacBio, ABI SOLID), in situ hybridization, bead-arraytechnologies (e.g., Luminex xMAP, Illumina BeadChips), branched DNAtechnology (e.g., Panomics, Genisphere).

The expressed target sequences can be directly detected and/orquantitated, or may be copied and/or amplified to allow detection ofamplified copies of the expressed target sequences or its complement. Insome embodiments, degraded and/or fragmented RNA can be usefullyanalyzed for expression levels of target sequences, for example RNAhaving an RNA integrity number of less than about 8.

In some embodiments, quantitative RT-PCR assays are used to measure theexpression level of at least one target sequence depicted in SEQ ID NOs:1-98. In other embodiments, a GeneChip or microarray can be used tomeasure the expression of one or more of the target sequences.

Molecular assays measure the relative expression levels of the targetsequences, which can be normalized to the expression levels of one ormore control sequences, for example array control sequences and/or oneor more housekeeping genes, for example GAPDH. Increased (or decreased)relative expression of the target sequences as described herein,including any of SEQ ID NOs:1-98, may thus be used alone or in anycombination with each other in the methods described herein. Inaddition, negative control probes may be included.

In alternative methods the expression level of a protein listed in TableA is determined. In some embodiments the protein comprises a sequence asset forth in any one of SEQ ID NOS: 99-195. Any suitable method known inthe art may be used to determine the protein expression level includingmass spectroscopy or an antibody assay such as in situ hybridization, aWestern blot, or an ELISA assay. Methods of generating antibodiesagainst the proteins listed in Table A are well within the level ofskill in the art. Skilled artisans will appreciate that in many assays amonoclonal antibody will be useful but is not necessarily required.

J. Diagnostic Samples

Diagnostic samples for use with the systems and in the methods of thepresent disclosure comprise nucleic acids suitable for providing RNAexpression information. The biological sample from which the expressedRNA is obtained and analyzed for target sequence expression is obtainedfrom the respiratory tract epithelium of the bronchi of a subject. Insome embodiments the sample is obtained from the bronchi walls of atleast one of sixth generation, seventh generation, and eighth generationbronchi of the subject. The diagnostic sample can be a biological sampleused directly in a method of the invention. Alternatively, thediagnostic sample can be a sample prepared from a biological sample.

The sample may be archival sample, having a known and documented medicaloutcome, or may be a sample from a current patient whose ultimatemedical outcome is not yet known. Samples to be analyzed for COPD aretypically obtained as airway epithelium brushings, for example.

The sample may initially be provided in a variety of states, as freshtissue, fresh frozen tissue, fine needle aspirates, and may be fixed orunfixed. Frequently, medical laboratories routinely prepare medicalsamples in a fixed state, which facilitates tissue storage. A variety offixatives can be used to fix tissue to stabilize the morphology ofcells, and may be used alone or in combination with other agents.Exemplary fixatives include crosslinking agents, alcohols, acetone,Bouin's solution, Zenker solution, Hely solution, osmic acid solutionand Carnoy solution.

Crosslinking fixatives can comprise any agent suitable for forming twoor more covalent bonds, for example an aldehyde. Sources of aldehydestypically used for fixation include formaldehyde, paraformaldehyde,glutaraldehyde or formalin. Preferably, the crosslinking agent comprisesformaldehyde, which may be included in its native form or in the form ofparaformaldehyde or formalin. One of skill in the art would appreciatethat for samples in which crosslinking fixatives have been used specialpreparatory steps may be necessary including for example heating stepsand proteinase-k digestion; see methods

One or more alcohols may be used to fix tissue, alone or in combinationwith other fixatives. Exemplary alcohols used for fixation includemethanol, ethanol and isopropanol.

Formalin fixation is frequently used in medical laboratories. Formalincomprises both an alcohol, typically methanol, and formaldehyde, both ofwhich can act to fix a biological sample.

Whether fixed or unfixed, the biological sample may optionally beembedded in an embedding medium. Exemplary embedding media used inhistology including paraffin, Tissue-Tek®, V.I.P.™, Paramat, ParamatExtra, Paraplast, Paraplast X-tra, Paraplast Plus, Peel Away ParaffinEmbedding Wax, Polyester Wax, Carbowax Polyethylene Glycol, Polyfin™,Tissue Freezing Medium TFM™, Cryo-Gel™, and OCT Compound (ElectronMicroscopy Sciences, Hatfield, Pa.). Prior to molecular analysis, theembedding material may be removed via any suitable techniques, as knownin the art. For example, where the sample is embedded in wax, theembedding material may be removed by extraction with organic solvent(s),for example xylenes. Kits are commercially available for removingembedding media from tissues. Samples or sections thereof may besubjected to further processing steps as needed, for example serialhydration or dehydration steps.

In some embodiments, the sample is a fixed, wax-embedded biologicalsample. Frequently, samples from medical laboratories are provided asfixed, wax-embedded samples, most commonly as formalin-fixed, paraffinembedded (FFPE) tissues.

Whatever the source of the biological sample, the target polynucleotidethat is ultimately assayed can be prepared synthetically (in the case ofcontrol sequences), but typically is purified from the biological sourceand subjected to one or more preparative steps. The RNA may be purifiedto remove or diminish one or more undesired components from thebiological sample or to concentrate it. Conversely, where the RNA is tooconcentrated for the particular assay, it may be diluted.

K. RNA Extraction

RNA can be extracted and purified from biological samples using anysuitable technique. A number of techniques are known in the art, andseveral are commercially available (e.g., FormaPure™ nucleic acidextraction kit, Agencourt Biosciences, Beverly Mass., High Pure FFPE RNAMicro Kit™, Roche Applied Science, Indianapolis, Ind.). RNA can beextracted from frozen tissue sections using TRIzol (Invitrogen,Carlsbad, Calif.) and purified using RNeasy Protect kit (Qiagen,Valencia, Calif.). RNA can be further purified using DNAse I treatment(Ambion, Austin, Tex.) to eliminate any contaminating DNA. RNAconcentrations can be made using a Nanodrop ND-1000 spectrophotometer(Nanodrop Technologies, Rockland, Del.). RNA integrity can be evaluatedby running electropherograms, and RNA integrity number (RIN, acorrelative measure that indicates intactness of mRNA) can be determinedusing the RNA 6000 PicoAssay for the Bioanalyzer 2100 (AgilentTechnologies, Santa Clara, Calif.).

L. Amplification and Hybridization

Following sample collection and nucleic acid extraction, the nucleicacid portion of the sample comprising RNA that is or can be used toprepare the target polynucleotide(s) of interest can be subjected to oneor more preparative reactions. These preparative reactions can includein vitro transcription (IVT), labeling, fragmentation, amplification andother reactions. mRNA can first be treated with reverse transcriptaseand a primer to create cDNA prior to detection, quantitation and/oramplification; this can be done in vitro with purified mRNA or in situ,e.g., in cells or tissues affixed to a slide.

By “amplification” is meant any process of producing at least one copyof a nucleic acid, in this case an expressed RNA, and in many casesproduces multiple copies. An amplification product can be RNA or DNA,and may include a complementary strand to the expressed target sequence.DNA amplification products can be produced initially through reversetranslation and then optionally from further amplification reactions.The amplification product may include all or a portion of a PSR, and mayoptionally be labeled. A variety of amplification methods are suitablefor use, including polymerase-based methods and ligation-based methods.Exemplary amplification techniques include the polymerase chain reactionmethod (PCR), the ligase chain reaction (LCR), ribozyme-based methods,self sustained sequence replication (3SR), nucleic acid sequence-basedamplification (NASBA), the use of Q Beta replicase, reversetranscription, nick translation, and the like.

Asymmetric amplification reactions may be used to preferentially amplifyone strand representing the PSR that is used for detection as the targetpolynucleotide. In some cases, the presence and/or amount of theamplification product itself may be used to determine the expressionlevel of a given PSR. In other instances, the amplification product maybe used to hybridize to an array or other substrate comprising sensorpolynucleotides which are used to detect and/or quantitate PSRexpression.

The first cycle of amplification in polymerase-based methods typicallyforms a primer extension product complementary to the template strand.If the template is single-stranded RNA, a polymerase with reversetranscriptase activity is used in the first amplification to reversetranscribe the RNA to DNA, and additional amplification cycles can beperformed to copy the primer extension products. The primers for a PCRmust, of course, be designed to hybridize to regions in theircorresponding template that will produce an amplifiable segment; thus,each primer must hybridize so that its 3′ nucleotide is paired to anucleotide in its complementary template strand that is located 3′ fromthe 3′ nucleotide of the primer used to replicate that complementarytemplate strand in the PCR.

The target polynucleotide can be amplified by contacting one or morestrands of the target polynucleotide with a primer and a polymerasehaving suitable activity to extend the primer and copy the targetpolynucleotide to produce a full-length complementary polynucleotide ora smaller portion thereof. Any enzyme having a polymerase activity thatcan copy the target polynucleotide can be used, including DNApolymerases, RNA polymerases, reverse transcriptases, enzymes havingmore than one type of polymerase or enzyme activity. The enzyme can bethermolabile or thermostable. Mixtures of enzymes can also be used.Exemplary enzymes include: DNA polymerases such as DNA Polymerase I(“Pol I”), the Klenow fragment of Pol I, T4, T7, Sequenase® T7,Sequenase® Version 2.0 T7, Tub, Tag, Tth, Pfx, Pfu, Tsp, Tfl, Tli andPyrococcus sp GB-D DNA polymerases; RNA polymerases such as E. coli,SP6, T3 and T7 RNA polymerases; and reverse transcriptases such as AMV,M-MuLV, MMLV, RNAse H.sup.-MMLV (SuperScript®), SuperScript® II,ThermoScript®, HIV-1, and RAV2 reverse transcriptases. All of theseenzymes are commercially available.

Exemplary polymerases with multiple specificities include RAV2 and Tli(exo-) polymerases. Exemplary thermostable polymerases include Tub, Tag,Tth, Pfx, Pfu, Tsp, Tfl, Tli and Pyrococcus sp. GB-D DNA polymerases.

Suitable reaction conditions are chosen to permit amplification of thetarget polynucleotide, including pH, buffer, ionic strength, presenceand concentration of one or more salts, presence and concentration ofreactants and cofactors such as nucleotides and magnesium and/or othermetal ions (e.g., manganese), optional cosolvents, temperature, thermalcycling profile for amplification schemes comprising a polymerase chainreaction, and may depend in part on the polymerase being used as well asthe nature of the sample. Cosolvents include formamide (typically atfrom about 2 to about 10%), glycerol (typically at from about 5 to about10%), and DMSO (typically at from about 0.9 to about 10%). Techniquesmay be used in the amplification scheme in order to minimize theproduction of false positives or artifacts produced duringamplification. These include “touchdown” PCR, hot-start techniques, useof nested primers, or designing PCR primers so that they form stem-loopstructures in the event of primer-dimer formation and thus are notamplified. Techniques to accelerate PCR can be used, for examplecentrifugal PCR, which allows for greater convection within the sample,and comprising infrared heating steps for rapid heating and cooling ofthe sample. One or more cycles of amplification can be performed. Anexcess of one primer can be used to produce an excess of one primerextension product during PCR; preferably, the primer extension productproduced in excess is the amplification product to be detected. Aplurality of different primers may be used to amplify different targetpolynucleotides or different regions of a particular targetpolynucleotide within the sample.

An amplification reaction can be performed under conditions which allowan optionally labeled sensor polynucleotide to hybridize to theamplification product during at least part of an amplification cycle.When the assay is performed in this manner, real-time detection of thishybridization event can take place by monitoring for light emission orfluorescence during amplification, as known in the art.

Where the amplification product is to be used for hybridization to anarray or microarray, a number of suitable commercially availableamplification products are available. These include amplification kitsavailable from NuGEN, Inc. (San Carlos, Calif.), including theWT-Ovation™ System, WT-Ovation™ System v2, WT-Ovation™ Pico System,WT-Ovation™ FFPE Exon Module, WT-Ovation™ FFPE Exon Module RiboAmp andRiboAmpPlus RNA Amplification Kits (MDS Analytical Technologies(formerly Arcturus) (Mountain View, Calif.), Genisphere, Inc. (Hatfield,Pa.), including the RampUp Plus™ and SenseAmp™ RNA Amplification kits,alone or in combination. Amplified nucleic acids may be subjected to oneor more purification reactions after amplification and labeling, forexample using magnetic beads (e.g., RNAClean magnetic beads, AgencourtBiosciences).

Multiple RNA biomarkers can be analyzed using real-time quantitativemultiplex RT-PCR platforms and other multiplexing technologies such asGenomeLab GeXP Genetic Analysis System (Beckman Coulter, Foster City,Calif.), SmartCycler® 9600 or GeneXpert® Systems (Cepheid, Sunnyvale,Calif.), ABI 7900 HT Fast Real Time PCR system (Applied Biosystems,Foster City, Calif.), LightCycler® 480 System (Roche Molecular Systems,Pleasanton, Calif.), xMAP 100 System (Luminex, Austin, Tex.) SolexaGenome Analysis System (Illumina, Hayward, Calif.), OpenArray Real TimeqPCR (BioTrove, Woburn, Mass.) and BeadXpress System (Illumina, Hayward,Calif.).

M. COPD Classification Arrays

The present disclosure contemplates that a COPD classification set orprobes derived therefrom may be provided in an array format. In thecontext of the present disclosure, an “array” is a spatially orlogically organized collection of polynucleotide probes. Any arraycomprising sensor probes specific for two or more of the targetsequences depicted in SEQ ID NOs: 1-98 or a product derived from thetarget sequences depicted therein can be used. Desirably, an array willbe specific for at least 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60,65, 70, 75, 80, 85, 90, 95 or all of SEQ ID NOs: 1-98. Expression ofthese sequences may be detected alone or in combination with othertranscripts. In some embodiments, an array is used which comprises awide range of sensor probes for COPD expression products, along withappropriate control sequences. An array of interest is the Human Exon1.0 ST Array (HuEx 1.0 ST, Affymetrix, Inc., Santa Clara, Calif.).

Typically the polynucleotide probes are attached to a solid substrateand are ordered so that the location (on the substrate) and the identityof each are known. The polynucleotide probes can be attached to one of avariety of solid substrates capable of withstanding the reagents andconditions necessary for use of the array. Examples include, but are notlimited to, polymers, such as (poly)tetrafluoroethylene,(poly)vinylidenedifluoride, polystyrene, polycarbonate, polypropyleneand polystyrene; ceramic; silicon; silicon dioxide; modified silicon;(fused) silica, quartz or glass; functionalized glass; paper, such asfilter paper; diazotized cellulose; nitrocellulose filter; nylonmembrane; and polyacrylamide gel pad. Substrates that are transparent tolight are useful for arrays that will be used in an assay that involvesoptical detection.

Examples of array formats include membrane or filter arrays (forexample, nitrocellulose, nylon arrays), plate arrays (for example,multiwell, such as a 24-, 96-, 256-, 384-, 864- or 1536-well, microtitreplate arrays), pin arrays, and bead arrays (for example, in a liquid“slurry”). Arrays on substrates such as glass or ceramic slides areoften referred to as chip arrays or “chips.” Such arrays are well knownin the art. In some embodiments the COPD classification array is a chip.

N. Data Analysis

Array data (or other expression data) can be managed and analyzed usingtechniques known in the art. The Genetrix suite of tools can be used formicroarray analysis (Epicenter Software, Pasadena, Calif.). Probe setmodeling and data pre-processing can be derived using the RobustMulti-Array (RMA) algorithm or variant GC-RMA, Probe LogarithmicIntensity Error (PLIER) algorithm or variant iterPLIER. Variance orintensity filters can be applied to pre-process data using the RMAalgorithm, for example by removing target sequences with a standarddeviation of <10 or a mean intensity of <100 intensity units of anormalized data range, respectively.

In some embodiments, one or more pattern recognition methods can be usedin analyzing the expression level of target sequences. The patternrecognition method can comprise a linear combination of expressionlevels, or a nonlinear combination of expression levels. In someembodiments, expression measurements for RNA transcripts or combinationsof RNA transcript levels are formulated into linear or non-linear modelsor algorithms (i.e., an “expression signature”) and converted into alikelihood score. This likelihood score indicates the probability that abiological sample is from a subject having COPD or at least one symptomthereof. The likelihood score can be used to distinguish classify COPD.The models and/or algorithms can be provided in machine readable format,and may be used to correlate expression levels or an expression profilewith a disease state, and/or to designate a treatment modality for asubject, patient, or class of subjects/patients.

Thus, results of the expression level analysis can be used to correlateincreased expression of one or more target sequences with COPD, and todesignate a treatment modality based on the classification. For example,the treatment modality may be initiating or ceasing treatment byadministration of at least one anti-COPD therapeutic agent.

Factors known in the art for diagnosing and/or suggesting, selecting,designating, recommending or otherwise determining a course of treatmentfor a patient or class of patients suspected of having COPD can beemployed in combination with measurements of the target sequenceexpression.

Certified tests for classifying COPD disease status and/or designatingtreatment modalities are also provided. A certified test comprises ameans for characterizing the expression levels of one or more of thetarget sequences of interest, and a certification from a governmentregulatory agency endorsing use of the test for classifying the COPDstatus of a biological sample.

In some embodiments, the certified test may comprise reagents foramplification reactions used to detect and/or quantitate expression ofthe target sequences to be characterized in the test. An array of probenucleic acids can be used, with or without prior target amplification,for use in measuring target sequence expression.

The test is submitted to an agency having authority to certify the testfor use in classifying COPD disease status of a subject. Results ofdetection of expression levels of the target sequences used in the testand correlation with disease status and/or outcome are submitted to theagency. A certification authorizing the diagnostic and/or prognostic useof the test is obtained.

Also provided are portfolios of expression levels comprising a pluralityof normalized expression levels of the target sequences describedherein, including SEQ ID NOs:1-98. Such portfolios may be provided byperforming the methods described herein to obtain expression levels froman individual patient or from a group of patients. The expression levelscan be normalized by any method known in the art; exemplarynormalization methods that can be used in various embodiments includeRobust Multichip Average (RMA), probe logarithmic intensity errorestimation (PLIER), non-linear fit (NLFIT) quantile-based and nonlinearnormalization, and combinations thereof. Background correction can alsobe performed on the expression data; exemplary techniques useful forbackground correction include mode of intensities, normalized usingmedian polish probe modeling and sketch-normalization.

In some embodiments, portfolios are established such that thecombination of genes in the portfolio exhibit improved sensitivity andspecificity relative to known methods. In considering a group of genesfor inclusion in a portfolio, a small standard deviation in expressionmeasurements correlates with greater specificity. Other measurements ofvariation such as correlation coefficients can also be used in thiscapacity. The invention also encompasses the above methods where thespecificity is at least about 50% and at least about 60%. The inventionalso encompasses the above methods where the sensitivity is at leastabout 90%.

The gene expression profiles of each of the target sequences comprisingthe portfolio can fixed in a medium such as a computer readable medium.This can take a number of forms. For example, a table can be establishedinto which the range of signals (e.g., intensity measurements)indicative of disease is input. Actual patient data can then be comparedto the values in the table to determine whether the patient samples arenormal, or indicate the presence of COPD. In a more sophisticatedembodiment, patterns of the expression signals (e.g., fluorescentintensity) are recorded digitally or graphically.

Comparisons can also be used to determine whether the patient is notlikely to experience COPD. The expression profiles of the samples arethen compared to a control portfolio. If the sample expression patternsare consistent with the expression pattern for COPD then (in the absenceof countervailing medical considerations) the patient is treated as onewould treat a COPD patient. If the sample expression patterns areconsistent with the expression pattern from the normal/control cell thenthe patient is diagnosed negative for COPD.

Genes can be grouped so that information obtained about the set of genesin the group can be used to make or assist in making a clinicallyrelevant judgment such as a diagnosis, prognosis, or treatment choice.

A patient report is also provided comprising a representation ofmeasured expression levels of a plurality of target sequences in abiological sample from the patient, wherein the representation comprisesexpression levels of target sequences corresponding to any one, two,three, four, five, six, eight, ten, twenty, thirty, fifty or more of thetarget sequences depicted in SEQ ID NOs: 1-98, or of the subsetsdescribed herein, or of a combination thereof. In some embodiments, therepresentation of the measured expression level(s) may take the form ofa linear or nonlinear combination of expression levels of the targetsequences of interest. The patient report may be provided in a machine(e.g., a computer) readable format and/or in a hard (paper) copy. Thereport can also include standard measurements of expression levels ofsaid plurality of target sequences from one or more sets of patientswith known COPD status and/or outcome. The report can be used to informthe patient and/or treating physician of the expression levels of theexpressed target sequences, the likely medical diagnosis and/orimplications, and optionally may recommend a treatment modality for thepatient.

Also provided are representations of the gene expression profiles usefulfor treating, diagnosing, prognosticating, and otherwise assessingdisease. In some embodiments, these profile representations are reducedto a medium that can be automatically read by a machine such as computerreadable media (magnetic, optical, and the like). The articles can alsoinclude instructions for assessing the gene expression profiles in suchmedia. For example, the articles may comprise a readable storage formhaving computer instructions for comparing gene expression profiles ofthe portfolios of genes described above. The articles may also have geneexpression profiles digitally recorded therein so that they may becompared with gene expression data from patient samples. Alternatively,the profiles can be recorded in different representational format. Agraphical recordation is one such format. Clustering algorithms canassist in the visualization of such data.

O. Kits

Kits for performing the desired method(s) are also provided, andcomprise a container or housing for holding the components of the kit,one or more vessels containing one or more nucleic acid(s), andoptionally one or more vessels containing one or more reagents. Thereagents include those described in the composition of matter sectionabove, and those reagents useful for performing the methods described,including amplification reagents, and may include one or more probes,primers or primer pairs, enzymes (including polymerases and ligases),intercalating dyes, labeled probes, and labels that can be incorporatedinto amplification products.

In some embodiments, the kit comprises primers or primer pairs specificfor those subsets and combinations of target sequences described herein.At least two, three, four or five primers or pairs of primers suitablefor selectively amplifying the same number of target sequence-specificpolynucleotides can be provided in kit form. In some embodiments, thekit comprises from five to fifty primers or pairs of primers suitablefor amplifying the same number of target sequence-representativepolynucleotides of interest.

The reagents may independently be in liquid or solid form. The reagentsmay be provided in mixtures. Control samples and/or nucleic acids mayoptionally be provided in the kit. Control samples may include tissueand/or nucleic acids obtained from or representative of the presence ofCOPD disease in a subject, as well as tissue and/or nucleic acidsobtained from or representative of the presence of COPD disease in asubject.

The nucleic acids may be provided in an array format, and thus an arrayor microarray may be included in the kit. The kit optionally may becertified by a government agency for use in classifying the diseasestatus of COPD tissue and/or for designating a treatment modality.

Instructions for using the kit to perform one or more methods of thedisclosure can be provided with the container, and can be provided inany fixed medium. The instructions may be located inside or outside thecontainer or housing, and/or may be printed on the interior or exteriorof any surface thereof. A kit may be in multiplex form for concurrentlydetecting and/or quantitating one or more different targetpolynucleotides representing the expressed target sequences.

P. Devices

Devices useful for performing methods of the disclosure are alsoprovided. The devices can comprise means for characterizing theexpression level of a target sequence of the invention, for examplecomponents for performing one or more methods of nucleic acidextraction, amplification, and/or detection. Such components may includeone or more of an amplification chamber (for example a thermal cycler),a plate reader, a spectrophotometer, capillary electrophoresisapparatus, a chip reader, and or robotic sample handling components.These components ultimately can obtain data that reflects the expressionlevel of the target sequences used in the assay being employed.

The devices may include an excitation and/or a detection means. Anyinstrument that provides a wavelength that can excite a species ofinterest and is shorter than the emission wavelength(s) to be detectedcan be used for excitation. Commercially available devices can providesuitable excitation wavelengths as well as suitable detectioncomponents.

Exemplary excitation sources include a broadband UV light source such asa deuterium lamp with an appropriate filter, the output of a white lightsource such as a xenon lamp or a deuterium lamp after passing through amonochromator to extract out the desired wavelength(s), a continuouswave (cw) gas laser, a solid state diode laser, or any of the pulsedlasers. Emitted light can be detected through any suitable device ortechnique; many suitable approaches are known in the art. For example, afluorimeter or spectrophotometer may be used to detect whether the testsample emits light of a wavelength characteristic of a label used in anassay.

The devices typically comprise a means for identifying a given sample,and of linking the results obtained to that sample. Such means caninclude manual labels, barcodes, and other indicators which can belinked to a sample vessel, and/or may optionally be included in thesample itself, for example where an encoded particle is added to thesample. The results may be linked to the sample, for example in acomputer memory that contains a sample designation and a record ofexpression levels obtained from the sample. Linkage of the results tothe sample can also include a linkage to a particular sample receptaclein the device, which is also linked to the sample identity.

The devices also comprise a means for correlating the expression levelsof the target sequences being studied with a classification of COPD.Such means may comprise one or more of a variety of correlativetechniques, including lookup tables, algorithms, multivariate models,and linear or nonlinear combinations of expression models or algorithms.The expression levels may be converted to one or more likelihood scores,reflecting the likelihood that the sample is from a subject with COPDand/or is from a subject without COPD. The models and/or algorithms canbe provided in machine readable format, and can optionally furtherdesignate a treatment modality for a patient or class of patients.

The device also comprises output means for outputting the COPD diseasestatus and/or a treatment modality. Such output means can take any formwhich transmits the results to a patient and/or a healthcare provider,and may include a monitor, a printed format, or both. The device may usea computer system for performing one or more of the steps provided.

Q. Methods of Treatment

The methods and systems of this disclosure also find use in conjunctionwith treatment of COPD in a subject. For example, the methods andsystems may be used to identify a subject or a class of subjects assuitable for treatment with at least one anti-COPD therapeutic agent.The methods and systems may also be used to monitor the response of apatient or a class of patients to treatment with at least one anti-COPDtherapeutic agent. As a result of the monitoring the treatment coursemay be modified, discontinued, or continued, for example.

Generally the treatment methods include providing a tissue sampleobtained from the respiratory tract epithelium of a subject. The methodsmay also include determining the expression level of at least onetranscript comprising (i) a sequence as set forth in any one of SEQ IDNOS. 1 to 98, (ii) a fragment of at least 100 nucleotides of a sequenceas set forth in any one of SEQ ID NOS. 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii), in the tissue sample to provide anexpression pattern profile. In some embodiments the expression level ofat least 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80,85, 90, 95 or 98 transcripts are determined, each such transcriptcomprising (i) a sequence as set forth in any one of SEQ ID NOS. 1 to98, (ii) a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS. 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii), in order to provide an expressionpattern profile. In some embodiments the expression level of at least 5,10, 15, 20, 25, 30, 35, 40, 45, 50 transcripts are determined, each suchtranscript comprising (i) a sequence as set forth in Table E, (ii) afragment of at least 100 nucleotides of a sequence as set forth in TableE, or (iii) a sequence with substantial homology to (i) or (ii), inorder to provide an expression pattern profile.

The methods may also include comparing the expression pattern profilewith a reference expression pattern profile. The methods may alsoinclude classifying the COPD status of the subject based on thecomparing. The methods may also include administering an anti-COPDtherapeutic agent to the subject if the subject is classified as havingactive COPD disease status warranting therapeutic intervention. Themethods may also include not administering an anti-COPD therapeuticagent to the subject if the subject is classified as not having activeCOPD disease status warranting therapeutic intervention. The methods mayalso include adjusting the dosing of the anti-COPD therapeutic agentbased on the classification of the COPD disease status of the subject.

EXAMPLES Methods

Patient Population

Bronchial airway brushings were obtained during bronchoscopy fromsubjects who were being followed longitudinally for the development oflung cancer at the British Columbia Cancer Research Agency between June2000 and May 2009 as part of the British Columbia Lung Health Study(Tammemagi M C, et al. 2011. Incremental value of pulmonary function andsputum DNA image cytometry in lung cancer risk prediction. Cancer PreyRes 4:552-561.) and the Pan-Canadian Lung Health Study. A total of 267bronchial brushing samples were selected to ensure matching forcovariates (Table 1). All subjects provided written informed consent.Institutional review board approval was obtained from participatinginstitutions. High molecular weight RNA isolated from the bronchialbrushings using the miRNeasy mini kit (Qiagen, Valencia, Calif.) wasprocessed and hybridized to Affymetrix Human Gene 1.0 ST Arrays.

Sample Collection

Brushings were obtained from the 6^(th) to 8^(th) generation bronchiusing a 1.5 mm brush, immediately placed in 1.5 mL RNALater (Qiagen) andstored at −80 C until processing. A detailed questionnaire was completedfor each subject which included age, race, ethnicity, a detailed smokinghistory, and medications. Spirometry was conducted as previouslydescribed (Tammemagi M C, et al. 2011. Incremental value of pulmonaryfunction and sputum DNA image cytometry in lung cancer risk prediction.Cancer Prey Res 4:552-561) using flow-sensitive spirometer (Presto FlashPortable Spirometer Version 1.2) according to the American ThoracicSociety recommendations. (1987. Standardization of spirometry—1987update. Statement of the American Thoracic Society. Am Rev Respir Dis136:1285-1298; 1995. Standardization of spirometry, 1994 Update.American Thoracic Society. Am J Respir Crit Care Med 152:1107-1136.)Percent emphysema was quantified by calculating the percentage of lowattenuation area on CT scan using a −950HU threshold as previouslydescribed. (Grydeland T B, et al. 2011. Quantitative CT measures ofemphysema and airway wall thickness are related to D(L)CO. Respir Med105:343-351; Grydeland T B, et al. 2010. Quantitative computedtomography measures of emphysema and airway wall thickness are relatedto respiratory symptoms. Am J Respir Crit Care Med 181:353-359.) Sampleswere selected on the basis of age, gender, smoking status, andpack-years of smoking to ensure that relevant co-variates were balancedbetween groups.

Sample Processing

High molecular weight RNA was isolated from the bronchial brushingsusing the miRNeasy mini kit (Qiagen) according to the manufacturer'sprotocol. Bronchial epithelial cells were lysed and homogenized inQIAzol Lysis Reagent. After chloroform extraction, the aqueous phase wasmixed with ethanol and applied to an RNeasy Mini Spin Column in order toretain high molecular weight RNA (>200 nt). Column flow-through wascollected, mixed with ethanol, and applied to an RNAEasy MinElute spincolumn to retain low molecular weight RNA. After washing, the high andlow molecular weight RNA fractions were separately eluted from thecolumns. Large and small RNA quantity and purity was assessed using aNanoDrop ND-1000 spectrophotometer, and integrity assessed using anAgilent 2100 BioAnalyzer.

High molecular weight RNA from bronchial epithelial brushings wasprocessed and hybridized to Affymetrix Human Gene 1.0 ST Arrays asdescribed in the GeneChip® Whole Transcript (WT) Sense Target LabelingAssay Manual (Affymetrix). A total of 200 ng of high molecular weightRNA was reverse transcribed (Whole Transcript cDNA Synthesis Kit,Affymetrix, Santa Clara, Calif.). This was followed by in vitrotranscription (IVT) (Whole Transcript cDNA Amplification Kit,Affymetrix, Santa Clara, Calif.), purification (GeneChip Sample CleanupModule), and reverse transcription with dUTP incorporation (WholeTranscript cDNA Synthesis Kit). The resulting single-stranded DNA wasfragmented using uracil DNA glycosylase (UDG) and apurinic/apyrimidinicendonuclease 1 (APE1), and labeled using DNA Labeling Reagent which iscovalently linked to biotin with terminal deoxynucleotidyl transferase(TdT) (Whole Transcript Terminal Labeling Kit, Affymetrix, Santa Clara,Calif.). IVT and cDNA fragmentation quality was determined using themRNA Nano Assay in the Agilent 2100 BioAnalyzer.

The labeled fragmented cDNA was hybridized to Affymetrix Human Gene 1.0ST Arrays for 16-18 hours in the GeneChip Hybridization Oven 640 at 45 Cwith 60 rpm rotation. After washing, the hybridized samples were stainedwith strepavidin (SAPE), followed by signal amplification with abiotinylated goat anti-streptavidin antibody and a second SAPE stainusing the Affymetrix Fluidics Station 450 (Hybridization Washing andStaining Kit, Affymetrix, Santa Clara, Calif.). Microarrays wereimmediately scanned using an Affymetrix GeneArray Scanner 3000 7G Plus(Affymetrix). (Zhang X, et al. 2010. Similarities and differencesbetween smoking-related gene expression in the nasal and bronchialepithelium. Physiol Genomics 41:1-8.)

Data Acquisition, Probeset Summarization and Normalization, and DataPreprocessing

A total of 269 arrays from 267 samples including two samples run induplicate were used for the generation of gene expression levels. Thearray data for two subjects were excluded due to sample annotationconcerns, leaving a total of 265 samples. To minimize the potentialconfounding effect of lung cancer, data from 19 subjects with adiagnosis of lung cancer as of January 2010 were excluded as were datafrom 8 subjects who lacked lung function testing within 1 year of theirstudy bronchoscopy, leaving a total of 238 samples.

Gene expression estimates were derived from the probe hybridizationintensities in the R statistical environment (R 2.9.2 and R 2.10.0) withthe aroma.affymetrix package v1.4.0 (Bengtsson H, Simpson K, Bullard J,and Hansen K. aroma.affymetrix: A generic framework in R for analyzingsmall to very large Affymetrix data sets in bounded memory. Tech Report#745. 2008. Department of Statistics, University of California,Berkeley) using the Robust Multichip Average algorithm and the EntrezGene Chip Definition File (CDF) v11.0.1. (Dai M, et al. 2005. Evolvinggene/transcript definitions significantly alter the interpretation ofGeneChip data. Nucleic Acids Research 33:e175.) Raw and processedmicroarray data has been deposited in the Gene Expression Omnibus (GEO)(GSE37147).

Microarray data quality was assessed using relative log expression (RLE)plots, normalized unscaled standard error (NUSE) plots, and principlecomponent analysis (PCA) of all genes across all samples. As anadditional quality control measure to exclude samples contaminated withinflammatory cells, hierarchical clustering was performed acrossepithelial and inflammatory cell specific genes as previously described.(Spira A, et al. 2004. Effects of cigarette smoke on the human airwayepithelial cell transcriptome. Proc Natl Acad Sci USA 101:10143-10148.)A metagene representing inflammatory cell specific gene expression wascalculated from the first principle component. The 238 samples from lungcancer-free current and former smokers with and without COPD were ofadequate quality for subsequent analysis (FIG. 1).

Using spirometry measurements obtained within 1 year of bronchoscopy,COPD was defined as the presence of both an FEV₁/FVC≦0.7 and FEV₁%predicted <80, based on standard reference equations. (Tammemagi M C, etal. 2011. Incremental value of pulmonary function and sputum DNA imagecytometry in lung cancer risk prediction. Cancer Prev Res 4:552-561;Crapo R O, Morris A H, and Gardner R M. 1981. Reference spirometricvalues using techniques and equipment that meet ATS recommendations. AmRev Respir Dis 123:659-664.) Age (at time of bronchoscopy), gender,smoking status (current or former smoker), and cumulative tobaccoexposure (calculated for the time of bronchoscopy) were used ascovariates using the 222 samples with complete covariate data. Foractive smokers, pack years at the time of bronchoscopy was calculatedfrom self-reported pack years at the time of last follow up, smokingduration and age at the time of last follow up, and age at the time ofsample collection. For the ANOVA, models 1a-1c (below) were eachcompared to model 2.

(1a) ge_(i)=β₀+β₁x_(Age)+β₂x_(Smoke) _(_)_(Status)+β₃x_(PY)+β₄x_(Gender)+β₅x_(COPD)+ε_(i)

(1b) ge_(i)=β₀+β₁x_(Age)+β₂x_(Smoke) _(_)_(Status)+β₃x_(PY)+β₄x_(Gender)+β₅x_(FEV1/FVC)+ε_(i)

(1c) ge_(i)=β₀+β₁x_(Age)+β₂x_(Smoke) _(_)_(Status)+β₃x_(PY)+β₄x_(Gender)+β₅x_(FEV1%)+ε_(i)

(2) ge_(i)=β₀+β₁x_(Age)+β₂x_(Smoke) _(_)_(Status)+β₃x_(PY)+β₄x_(Gender)+ε_(i)

In these models, ge_(i) represents the log2-expression of gene i andε_(i) represents the error assumed to be normally distributed. The falsediscovery rates (FDR) of the p-values from each ANOVA were calculatedusing the method of Benjamini and Hochberg. (Benjamini Y and Hochberg Y.1995. Controlling the false discovery rate: a practical and powerfulapproach to multiple testing. J R Statist Soc 57:289-300.) Expressionprofiles of genes associated with COPD and continuous measures of lungfunction were organized by hierarchical clustering of z-score normalizedrelative expression levels using complete linkage clustering with aEuclidean distance metric. Cluster membership based on gene expressionamong individuals with COPD was determined using the cuttree function.

Genes whose expression levels were associated with COPD and/orcontinuous measures of lung function were identified by an ANOVA FDR of<0.05 and a linear fold change (FC) of >1.25 between COPD and No COPDafter controlling for major demographic variables and risk factors forCOPD.

Enrichment Analysis

Analysis to determine functional enrichment among the 98 genes whoseexpression was associated with COPD was performed using DAVID 6.7b.(Dennis G, et al. DAVID: Database for Annotation, Visualization, andIntegrated Discovery. Genome Biol 4[5], P3. 2003.) Transcription factorbinding site enrichment analysis was performed using GATHER. (GATHER: asystems approach to interpreting genomic signatures. 2006. Chang J T;Nevins J R. Bioinformatics 22:2926-2933.) Additional predicted targetsof selected transcription factors were identified with patser usingTransfac version 12.1. (Matys V, et al. 2006. TRANSFAC and its moduleTRANSCompel: transcriptional gene regulation in eukaryotes. NucleicAcids Res 34 (Database issue):D108-110; Hertz G Z and Stormo G D. 1999.Identifying DNA and protein patterns with statistically significantalignments of multiple sequences. Bioinformatics 15:563-577.) GSEA wasused to determine the relationship between our results and previouslypublished studies as detailed in the supplementary methods and Table 2.A false-discovery rate threshold of FDR <0.05 was used to determinesignificant enrichment by GSEA.

TABLE 2 Summary of study designs of previously published lung tissuegene expression studies in COPD Patient Sample Sample COPD Studypopulation type size Definitions GSE1122 Undergoing lung Explanted lungN = 5 Severe (Golpon H A, transplantation, tissue or emphysema emphysemaet al. 2004. or healthy donors surgically N = 6 alpha1 Emphysema whoselungs resected lung antitrypsin Lung Tissue could not be used deficiencyGene for transplant N = 5 controls Expression Profiling. Am J RespirCell Mol Biol 31: 595- 600.) GSE8500 Surgical resection Surgically N = 3GOLD3 GOLD (Wang I M, et of lung nodules resected lung N = 10 GOLD2classification al. 2008. Gene tissue N = 9 GOLD1 Expression N = 21 GOLD0Profiling in N = 5 Patients with nonsmokers* Chronic ObstructivePulmonary Disease and Lung Cancer. Am J Respir Crit Care Med 177: 411)GSE8581 Surgical resection Histologically N = 15 cases FEV1/FVC(Bhattacharya of a lung nodule normal tissue N = 18 controls <0.7 andFEV1 S, et al. 2009. suspected to be distant from the N = 23 <70%predicted Molecular cancer tumor margin unclassified^(†) biomarkers forquantitative and discrete COPD phenotyes. Am J Respir Cell Mol Biol 40:359-367) G5E1650 Cases: lung Surgically N = 20 severe FEV1 <50% (SpiraA, et al. volume reduction resected lung emphysema predicted 2004. Genesurgery tissue N = 14 controls Expression Controls: Profiling ofthoracotomy for Human Lung suspicion of Tissue from malignancy Smokerswith Severe Emphysema. Am J Respir Cell Mol Biol 31: 601-610) Ning etal. Surgical lung Surgically N = 14 moderate GOLD PNAS 2004 specimensresected lung (GOLD2) classification (Ning W, et al. tissue COPD 2004. N= 12 controls Comprehensive gene expression profiles reveal pathwaysrelated to the pathogenesis of chronic obstructive pulmonary disease.Proc Natl Acad Sci USA 101: 14895- 14900) GSE27597 Undergoing lung Lungtissue N = 6 severe Mean linear (Campbell J D, transplantation, coresfrom emphysema intercept et al. 2012. A or healthy donors explanted lungN = 2 controls gene expression whose lungs signature of could not beused emphysema- for transplant related lung destruction and its reversalby the tripeptide GHK. Genome Med 4: 67)

Enrichment analysis of other gene expression datasets was performedusing GSEA v2.07. (Mootha V K, et al. 2003. PGC-1α-responsive genesinvolved in oxidative phosphorylation are coordinately downregulated inhuman diabetes. Nature Genetics 34:267-273; Subramanian A, et al. 2005.Gene set enrichment analysis: A knowledge-based approach forinterpreting genome-wide expression profiles. Proc Natl Acad Sci USA102:15545-15550.) Enrichment p-values were calculated by gene setpermutation (n=1000), and significant enrichment was determined by anFDR-corrected p-value of <0.05. The core enrichment genes, or leadingedge subset, were defined by GSEA as the genes with the mostcontribution to the significant enrichment. To determine whetherpredicted transcription factor binding sites were enriched in theregulatory regions of the airway COPD gene-expression signature,analysis was performed using GATHER. (GATHER: a systems approach tointerpreting genomic signatures. 2006. Chang J T; Nevins J R.Bioinformatics 22:2926-2933.) Significant enrichment was determinedusing a Bayes Factor of ≧6 and a p-value of <0.05.

GSE5058:

To determine whether COPD-associated changes in bronchial airway geneexpression are concordant with those that occur in the small airwayepithelium (10-12th generation bronchi), we examined a dataset ofsmall-airway gene expression associated with COPD. (Tilley A E, et al.2009. Down-regulation of the Notch pathway in human airway epithelium inassociation with smoking and chronic obstructive pulmonary disease. Am JRespir Crit Care Med 179:457-466.) Data was normalized using the RMAalgorithm and Entrez Gene CDF v11.0.1. (Dai M, et al. 2005. Evolvinggene/transcript definitions significantly alter the interpretation ofGeneChip data. Nucleic Acids Research 33:e175.) Genes were rankedaccording to the t-statistic from a t-test comparing small airway geneexpression from subjects with GOLD1-2 COPD (n=4) and healthy subjectswith normal lung function (n=12). GSEA was used to compare this rankedlist to the genes significantly altered in association with COPD in ourstudy.

GSE1122, GSE8500, GSE8581, GSE1650:

To determine the relationship between COPD-associated changes in airwaygene expression and gene expression changes in the more distal lungparenchyma, we re-analyzed several previously published gene expressiondatasets as previously described. (Campbell J D, et al. 2012. A geneexpression signature of emphysema-related lung destruction and itsreversal by the tripeptide GHK. Genome Med 4:67.) Briefly, raw dataobtained from the Gene Expression Omnibus (GEO) were normalized usingRMA and the Entrez Gene CDF v11.0.1. Data was analyzed using linearmodels including terms for COPD-related clinical variables availablethrough GEO. For each dataset, gene expression profiles were rankedaccording to the association with categorical and continuous measures ofCOPD and lung function. GSEA was used to compare these ranked lists tothe genes significantly altered in association with COPD in our study.GSEA was also used to compare a ranked list of COPD-associated changesin airway gene expression to the genes whose expression levels in thelung parenchyma were previously reported to be associated with COPD.(Spira A, et al. 2004. Gene Expression Profiling of Human Lung Tissuefrom Smokers with Severe Emphysema. Am J Respir Cell Mol Biol31:601-610; Bhattacharya S, et al. 2009. Molecular biomarkers forquantitative and discrete COPD phenotyes. Am J Respir Cell Mol Biol40:359-367; Ning W, et al. 2004. Comprehensive gene expression profilesreveal pathways related to the pathogenesis of chronic obstructivepulmonary disease. Proc Natl Acad Sci USA 101:14895-14900; Golpon H A,et al. 2004. Emphysema Lung Tissue Gene Expression Profiling. Am JRespir Cell Mol Biol 31:595-600; Wang I M, et al. 2008. Gene ExpressionProfiling in Patients with Chronic Obstructive Pulmonary Disease andLung Cancer. Am J Respir Crit Care Med 177:411.

GSE27597:

We also sought to investigate the relationship between COPD-associatedchanges in airway gene expression and a model of disease progression(GSE27597). (Campbell J D, et al. 2012. A gene expression signature ofemphysema-related lung destruction and its reversal by the tripeptideGHK. Genome Med 4:67.) This dataset modeled emphysema progression byprofiling multiple lung parenchymal cores from six individuals withadvanced COPD and two individuals without COPD. These cores representeda range of emphysema severities, quantified by the mean linear intercept(Lm), within each individual. Raw data were normalized using RMA, andanalyzed using a linear mixed effects model including fixed effects forLm and lung slice from which the core was obtained, and a random patienteffect. Gene expression profiles were ranked according to associationwith Lm. GSEA was used to compare this ranked list to airway geneexpression significantly altered in COPD.

Real Time PCR Validation of Gene Expression Associated with COPD

To confirm COPD-associated gene expression changes, quantitativereal-time PCR (qRT-PCR) was performed as previously described. (Beane J,et al. 2011. Characterizing the impact of smoking and lung cancer on theairway transcriptome using RNA-Seq. Cancer Prey Res 4:803-817.) Relativeexpression of DUSP5, TMPRSS11D, SERPINB13, WIF1, and CLDN8 wascalculated using the ΔΔCt method and 18S expression for normalization.Relative expression of PTGS2, NR4A1, C8orf4, and FOS was calculatedusing the ΔΔCt method and GAPDH expression for normalization.

Gene Expression Changes Associated With ATF4 Overexpression

To determine the relationship between ATF4 expression and the airwayCOPD signature, we overexpressed ATF4 in immortalized human bronchialepithelial cells (BEAS2B). BEAS2B cells were cultured in BEGM growthmedium (Lonza) and plated at an 80% confluence in 6-well plates 24 hbefore transfection. 3 ug of the plasmid SC119103 (human ATF4 cDNAcloned into a pCMV6-XL5 vector backbone; Origene) was transfected intothe cells in triplicate using Lipofectamine 2000 (Invitrogen) as permanufacturer's protocol. 3 ug of an empty pCMV6-XL5 vector (Origene) wastransfected into the cells in triplicate as a negative controls. Cellswere harvested at 24 hours post-transfection and total RNA was isolatedusing the miRNeasy mini kit (Qiagen), ATF4 over-expression was confirmedby qRT-PCR (FIG. 6). Briefly, RNA was reverse transcribed using the RT²First Strand Kit (QIAQEN) and 4.5 ng of starting cDNA product togetherwith 1 ul of 10 uM RT² qPCR primer assay were added to the RT² SYBRGreen Mastermix (QIAGEN) as per manufacturer's protocol. Amplification(40 cycles), data acquisition, and data analysis were carried out usingthe StepOne Real Time PCR System (Applied Biosystems). Relativeexpression was calculated using the ΔΔCt method.

Total RNA was isolated from the BEAS2B cells transfected with ATF4 (n=3)or empty vector (n=3) at the 24 hour time point, processed, labeled, andhybridized to Affymetrix Human Gene 1.0 ST Arrays. Raw data werenormalized using the RMA algorithm and Entrez Gene CDF v11.0.1⁸. (Dai M,et al. 2005. Evolving gene/transcript definitions significantly alterthe interpretation of GeneChip data. Nucleic Acids Research 33:e175.)Gene expression differences induced by ATF4 overexpression weredetermined by t-test. Enrichment of the airway COPD signature amongBEAS2B gene expression levels ranked according to association with ATF4overexpression COPD was determined using GSEA.

Reversibility of COPD-Associated Airway Epithelial Gene Expression

GSE36221:

To determine the relationship between airway epithelial gene expressiondifferences associated with COPD and treatment, we leveraged microarraydata from 162 endobronchial biopsy samples obtained longitudinally fromindividuals with COPD randomized to receive fluticasone with (n=25patients, n=61 samples) or without (n=20 patients, n=46 samples)salmeterol, or placebo (n=23 patients, n=55 samples) (Lapperre T S, etal, and Groningen Leiden Universities Corticosteroids in ObstructiveLung Disease Study Group. 2009. Effect of fluticasone with and withoutsalmeterol on pulmonary outcomes in chronic obstructive pulmonarydisease: a randomized trial. Ann Intern Med 151:517-527) (GSE36221) aspart of the GLUCOLD trial (ClinicalTrials.gov registration number:NCT00158847) (FIG. 1). Samples were obtained a baseline prior totreatment, and at 6-months and 30-months after the initiation oftreatment. After adjusting for RNA quality as measured by RIN and forpatient, genes were ranked according to the t-statistic for longitudinalgene expression associated with fluticasone-containing treatment.Enrichment of airway epithelial gene expression associated with COPD wasdetermined using GSEA, with an FDR <0.05 indicating significantenrichment.

GSE4302:

To identify a fluticasone-specific pattern of gene expression, weexamined data from a whole-genome gene expression study of bronchialbrushings obtained from asthmatics before and after treatment withfluticasone. (Woodruff P G, et al. 2007. Genome-wide profilingidentifies epithelial cell genes associated with asthma and withtreatment response to corticosteroids. Proc Natl Acad Sci USA104:15858-15863.) Raw data were normalized using the RMA algorithm andEntrez Gene CDF v11.0.1. (Dai M, et al. 2005. Evolving gene/transcriptdefinitions significantly alter the interpretation of GeneChip data.Nucleic Acids Research 33:e175.) Data from before and after treatmentwith fluticasone (n=19) or placebo (n=13) were analyzed using a linearmixed effects model including terms for time, treatment, and theinteraction between time and treatment. Gene expression was rankedaccording to the magnitude of fluticasone-associated changes using thet-value for the time:treatment interaction term. Enrichment of theairway COPD signature among fluticasone-associated gene expressionchanges was determined using GSEA.

EXAMPLE 1 Characteristics of the Study Population

There were no significant differences in age, cumulative smokingexposure, or smoking status between the 87 subjects with COPD and the151 subjects without COPD (Table 1). Subjects with COPD had lower FEV1%predicted and FEV1/FVC than the control group. The FEV1 across subjectswith COPD ranged from 15-79% of the reference value, with most COPDsubjects having moderate disease (Global Initiative for Obstructive LungDisease (GOLD) Grade 2) (Global initiative for chronic obstructive lungdisease. 2011. Global initiative for chronic obstructive lung disease:Global strategy for the diagnosis, management, and prevention of chronicobstructive pulmonary disease.) as would be expected from abronchoscopy-based cohort. A minority of the study population usedinhaled corticosteroids or inhaled bronchodilators, with a statisticallysignificant association with COPD status. Of the 14 subjects withoutCOPD taking an inhaled medication, 3 had a history of asthma. A total of17 subjects (8 with COPD and 9 without COPD) reported a history ofasthma. Groups also differed with respect to statin use. There was nosignificant difference in the use of non-steroidal anti-inflammatorydrugs (NSAID).

TABLE 1 Clinical Characteristics of the Study Population COPD No COPD (n= 87)^(‡) (n = 151)^(‡) P-value* Age in years 65 (6) 64 (6)    0.25Gender 52 Male 83 Male    0.5 35 Female 68 Female Smoking 30 Current 69Current    0.1 Status 57 Former 82 Former Pack Years 51 (25)^(†) 47(19)^(†)    0.11 FEV₁% 60 (14) 93 (13) <10⁻⁴ predicted FEV₁/FVC 0.56(0.09) 0.75 (0.06) <10⁻⁴ Years since 11.84 (9.86) 11.11 (6.73)    0.52smoking cessation Inhaled 18 (21%) 7 (5%) <10⁻³ corticosteroid useInhaled 21 (24%) 11 (7%) <10⁻³ bronchodilator use Statin use 23 (26%) 23(15%)    0.041 Nonsteroidal 21 (24%) 46 (30%)    0.37 anti-inflammatorydrug (NSAID) use The mean and standard deviation are shown forcontinuous variables. *P-values were calculated using a Student's t-testor Fisher exact test. ^(†)Missing PY for 5 subjects with COPD, and 11subjects without COPD ^(‡)97% of the subjects were Caucasian

EXAMPLE 2 Bronchial Epithelial Gene Expression Associated With COPD andContinuous Measures of Lung Function

The expression levels of 107 genes were associated with COPD (FDR<0.05and FC>1.25) after adjusting for major demographic variables and riskfactors for COPD including age, gender, smoking status and cumulativesmoke exposure. The expression levels of 110 genes were associated withFEV₁% predicted, and 102 with FEV₁/FVC as continuous measures. Theexpression profiles of 98 genes were associated with all three measures;54 of these genes were increased, and 44 were decreased in COPD (FIG.2). This bronchial airway signature of COPD includesdihydropyrimidinase-like 3 (DPYSL3), CEACAM5, Sushi-repeat containingprotein X-linked (SRPX), and enoyl-CoA delta isomerase 2 (PECI), fourgenes described in prior studies as irreversibly altered by cigarettesmoke even decades after smoking cessation. (Beane J, et al. 2007.Reversible and permanent effects of tobacco smoke exposure on airwayepithelial gene expression. Genome Biol 8:R201; and Spira A, et al.2004. Effects of cigarette smoke on the human airway epithelial celltranscriptome. Proc Natl Acad Sci USA 101:10143-10148.) Amongindividuals with COPD, cluster membership in FIG. 2 was significantlyassociated with FEV1% predicted but not other clinical co-variates orRNA quality (Table 3). Further analysis of potential sources of the geneexpression variability within classes is presented below.

TABLE 3 Association of COPD Sample Clusters With Clinical Co-VariatesCOPD Cluster 1 Cluster 2 (n = 40) (n = 47) P-Value* Age 64 (6) 66 (6)0.29 Sex 21 Male 31 Male 0.27 19 Female 16 Female Smoking Status 17Current 13 Current 0.18 23 Former 34 Former Pack Years 52 (18)* 50 (29)*0.73 FEV1% 56 (15) 64 (11) 0.0038 FEV1/FVC 58 (10) 61 (8) 0.14 %Emphysema 10 (6)^(†) 14 (10)^(†) 0.08 Inhaled corticosteroid 9  9 0.79use Inhaled 9 10 0.13 bronchodilator use Statin use 7 16 0.09 NSAID use8 13 0.46 RNA Integrity 8 (1)^(‡) 8 (1)^(‡) 0.49 Number The mean andstandard deviation are shown for continuous variables. *Cluster 1missing three values. Cluster 2 missing two values. ^(†)Cluster 1missing sixteen values. Cluster 2 missing five values. ^(‡)Cluster 1missing eighteen values. Cluster 2 missing thirteen values.

To determine whether asthma, inhaled medications, statin use, or themethod of COPD classification affected this analysis, we repeated theanalysis excluding individuals with a self-reported history of asthma(n=17), individuals using an inhaled corticosteroid or bronchodilator(n=37), individuals using a statin medication (n=46), or individualswith mild decreases in FEV₁% predicted (range: 70-80%) (n=49). Weidentified a consistent relationship between COPD-associated changes inairway gene expression in each of these analyses, with 80-99% of the 98COPD-associated genes also showing an FDR<0.05 and FC>1.25 in theseanalyses (Table 4). We did not detect significant correlation of ametagene summarizing the COPD airway gene expression signature withyears since quitting smoking among former smokers (p>0.05). We alsofailed to detect significant association between COPD status and ametagene representing inflammatory cell-specific gene expression. (SpiraA, et al. 2004. Effects of cigarette smoke on the human airwayepithelial cell transcriptome. Proc Natl Acad Sci USA 101:10143-10148.)When the inflammatory cell metagene was included as a covariate in thelinear model, all 98 COPD-associated genes remained significant atFDR<0.05 and FC>1.25.

TABLE 4 Concordance of COPD-Associated Bronchial Airway Gene ExpressionChanges in Sub-Group Analyses Number of Overlap with Sample size ofCOPD-associated 98-gene COPD Samples excluded sub-groups genes*signature History of asthma  79 COPD 95 96% (94/98) (n = 17) 142 NoCOPDInhaled medications  64 COPD 78 80% (78/98) (n = 37) 137 NoCOPD Statinmedications  64 COPD 96 96% (94/98) (n = 46) 128 NoCOPD Mild decrease in 62 COPD 99 99% (97/98) FEV₁% predicted 127 NoCOPD (n = 49) *Significant association of gene expression with COPD and continuousmeasures of lung function was determined as described in the methods.

To computationally validate the association of these genes with COPD, weperformed Gene Set Enrichment Analysis (GSEA) using a publicly-availablewhole-genome gene-expression dataset of small airway epithelium(10th-12th generation bronchi) that included 12 healthy smokers and 4smokers with COPD in GOLD Grade 1-2 severity (GSE5058). (Tilley A E, etal. 2009. Down-regulation of the Notch pathway in human airwayepithelium in association with smoking and chronic obstructive pulmonarydisease. Am J Respir Crit Care Med 179:457-466.) We identified aconcordant relationship between the 98 genes whose expression patternswere associated with COPD in the present study and COPD-associated geneexpression differences observed in this dataset (FDR_(GSEA)<0.05; FIG.3). We also experimentally validated the COPD-associated expressionpattern of 9 genes via qRT-PCR (FIG. 4). Together, these data identify aCOPD-associated bronchial airway field of injury that reflects thepresence and severity of COPD and that is consistent withCOPD-associated gene expression changes in 10th to 12th generationbronchi. This finding is unexpected and surprising and identifies thesegenes as useful markers of COPD disease status.

To explore the biologic function of the 98 genes whose expression levelswere associated with COPD, FEV₁% predicted, and FEV₁/FVC, genes weresubdivided into two groups: 1) higher expression in COPD and 2) lowerexpression in COPD (FIG. 2). Both lists were significantly enriched forgenes belonging to a variety of functional categories (Table 5)including glycoproteins (up-regulated), proteins involved in the acuteinflammatory response (up-regulated), and EGF-like domains(down-regulated). These findings suggest that these gene expressionchanges reflect COPD-associated alterations in processes related to theinflammatory response and regulation of cell growth in bronchial airwayepithelium.

TABLE 5 Functional Enrichment Among the 98 Genes Whose Expression in theBronchial Epithelium is Associated With COPD Modified Fisher ExactBenjamini Gene Cluster Enriched Category P-Value P-Value Up-regulated inglycoprotein (SP_PIR_KEYWORD) 3.30*10⁻⁶ 1.20*10⁻³ COPD SAA (SMART)2.10*10⁻⁷ 2.40*10⁻³ PIRSF002472: Serum amyloid A 6.00*10⁻⁷ 2.60*10⁻³(PIR_SUPERFAMILY) PIRSF002472: amyloid protein, SAA type 2.40*10⁻⁷3.10*10⁻³ (PIR_SUPERFAMILY) acute phase (SP_PIR_KEYWORD) 1.1010⁻⁶4.80*10⁻³ signal (SP_PIR_KEYWORDS) 1.70*10⁻⁴ 1.50*10⁻² Secreted(SP_PIR_KEYWORDS) 1.10*10⁻⁴ 1.80*10⁻² hdl (SP_PIR_KEYWORDS) 1.50*10⁻⁵3.20*10⁻² polymorphism (SP_PIR_KEYWORDS) 1.20*10⁻³ 4.20*10⁻² amyloid(SP_PIR_KEYWORDS) 4.10*10⁻⁵ 4.30*10⁻² glycosylation site: N-linked(GlcNAc . . . ) 2.20*10⁻⁴ 4.70*10⁻² (UP_SEQ_FEATURE) disulfide bond(SP_PIR_KEYWORDS) 1.30*10⁻³ 5.30*10⁻² insoluble fraction (GOTERM_CC_FAT)1.10*10⁻³ 7.30*10⁻² membrane fraction (GOTERM_CC_FAT) 8.70*10⁻⁴7.70*10⁻² plasma liproprotein particle 1.90*10⁻⁴ 7.90*10⁻²(GOTERM_CC_FAT) protein-lipid complex (GOTERM_CC_FAT) 1.90*10⁻⁴7.90*10⁻² signal peptide (UP_SEQ_FEATURE) 1.90*10⁻⁴ 8.70**10⁻²Down-regulated secreted (SP_PIR_KEYWORDS) 1.80*10⁻⁴ 6.50**10⁻² in COPDsignal (SP_PIR_KEYWORDS) 8.40*10⁻⁴ 6.80*10⁻² differentiation(SP_PIR_KEYWORDS) 4.60*10⁻⁴ 7.40*10⁻² egf-like domain (SP_PIR_KEYWORDS)1.40*10⁻⁴ 7.50*10⁻²

Table A lists the 98 genes whose expression levels were associated withCOPD status, identified by Probeset ID (col. 1), Gene Symbol (col. 2),and Entrez Gene ID (col. 3). The sequences for each gene (SEQ ID NOS:1-98; Table A, col. 4) and the protein encoded by each gene (SEQ ID NOS:99-195; Table A, col. 5) are presented in the Sequence Listing. (TPRXL(Entrez Gene ID 348825) is a non-coding RNA so there is no correspondingprotein sequence.) The sixth column of Table A indicates whether thegene is upregulated (up) or downregulated (down) in airway epithelia ofsubjects with COPD.

TABLE A Gene Sequence Protein Sequence Entrez IdentificationIdentification Direction in Probe ID Gene Symbol Gene ID Number NumberCOPD  10242_at KCNMB2 10242 1 99 down  10321_at CRISP3 10321 2 100 down 10391_at CORO2B 10391 3 101 down  10449_at ACAA2 10449 4 102 down 10455_at PECI 10455 5 103 down  1048_at CEACAM5 1048 6 104 up  10643_atIGF2BP3 10643 7 105 up  11074_at TRIM31 11074 8 106 up  11197_at WIF111197 9 107 down  11213_at IRAK3 11213 10 108 up 117156_at SCGB3A2117156 11 109 down 131450_at CD200R1 131450 12 110 up 135228_at CD109135228 13 111 up  1562_at CYP2C18 1562 14 112 up 158471_at PRUNE2 15847115 113 down 160728_at SLC5A8 160728 16 114 up  1809_at DPYSL3 1809 17115 up  1825_at DSC3 1825 18 116 up  1836_at SLC26A2 1836 19 117 up 1847_at DUSP5 1847 20 118 up  2037_at EPB41L2 2037 21 119 down219970_at GLYATL2 219970 22 120 up 220416_at LRRC63 220416 23 121 down221395_at GPR116 221395 24 122 down  23089_at PEG10 23089 25 123 down 23120_at ATP10B 23120 26 124 up  2353_at FOS 2353 27 125 up  2525_atFUT3 2525 28 126 up  2565_at GABRG1 2565 29 127 down  2568_at GABRP 256830 128 up  2571_at GAD1 2571 31 129 up  25849_at DKFZP564O0823 25849 32130 up  26154_at ABCA12 26154 33 131 up  27286_at SRPX2 27286 34 132 up 28234_at SLCO1B3 28234 35 133 up  2922_at GRP 2922 36 134 down  3043_atHBB 3043 37 135 up  3164_at NR4A1 3164 38 136 up  3371_at TNC 3371 39137 up 342035_at GLDN 342035 40 138 down 345275_at HSD17B13 345275 41139 down 348825_at TPRXL 348825 42 up  3620_at INDO 3620 43 140 up389136_at VGLL3 389136 44 141 down  3934_at LCN2 3934 45 142 up400986_at LOC400986 400986 46 143 up  4036_at LRP2 4036 47 144 down404220_at C6orf201 404220 48 145 down  4057_at LTF 4057 49 146 down 4256_at MGP 4256 50 147 down 440603_at BCL2L15 440603 51 148 up 4543_at MTNR1A 4543 52 149 up  4585_at MUC4 4585 53 150 up  4883_atNPR3 4883 54 151 down  5172_at SLC26A4 5172 55 152 up  5275_at SERPINB135275 56 153 up  5321_at PLA2G4A 5321 57 154 up  53842_at CLDN22 53842 58155 down  54575_at UGT1A10 54575 59 156 up  55086_at CXorf57 55086 60157 down   552_at AVPR1A 552 61 158 down  55885_at LMO3 55885 62 159down  56169_at GSDMC 56169 63 160 up  56667_at MUC13 56667 64 161 up 56892_at C8orf4 56892 65 162 up  56938_at ARNTL2 56938 66 163 up 5737_at PTGFR 5737 67 164 down  5743_at PTGS2 5743 68 165 up  57718_atKIAA1622 57718 69 166 down  60494_at CCDC81 60494 70 167 down  6288_atSAA1 6288 71 168 up  6289_at SAA2 6289 72 169 up   629_at CFB 629 73 170up  6291_at SAA4 6291 74 171 up  63895_at FAM38B 63895 75 172 down 64759_at TNS3 64759 76 173 down 653198_at LOC653198 653198 77 174 down 6947_at TCN1 6947 78 175 up  7092_at TLL1 7092 79 176 down   729_at C6729 80 177 down  7348_at UPK1B 7348 81 178 up  7850_at IL1R2 7850 82 179up  79625_at C4orf31 79625 83 180 down  79820_at CATSPERB 79820 84 181up  80206_at FHOD3 80206 85 182 down  8190_at MIA 8190 86 183 up 84419_at C15orf48 84419 87 184 up  8471_at IRS4 8471 88 185 down 84911_at ZNF382 84911 89 186 down  85479_at DNAJC5B 85479 90 187 down 8710_at SERPINB7 8710 91 188 down  8910_at SGCE 8910 92 189 down 9073_at CLDN8 9073 93 190 down  9245_at GCNT3 9245 94 191 up  9353_atSLIT2 9353 95 192 down  9407_at TMPRSS11D 9407 96 193 up  9723_at SEMA3E9723 97 194 down  9982_at FGFBP1 9982 98 195 up

EXAMPLE 3 ATF4 as a Mediator of Airway Gene-Expression AlterationsAssociated with COPD

To explore potential regulators of COPD-associated changes in geneexpression, we used GATHER to identify transcription factor bindingsites enriched in the regulatory regions of differentially expressedgenes. We identified enrichment of binding sites for ATF4 and CREB1among the 98 genes with COPD-associated expression differences (p<0.001)(Table 6). To explore a potential mechanistic role for ATF4 inregulating COPD-associated gene expression differences, we examined theeffects of overexpressing ATF4 in the BEAS2B bronchial epithelium cellline and found that this resulted in an increase in many of the samegenes that are expressed at higher levels in the bronchial airway ofindividuals with COPD (FIG. 5A; FIG. 6). Furthermore, all 13 of the coreenrichment genes increased by both ATF4 overexpression and in the airwayCOPD signature are predicted targets of ATF4 (FIG. 5B-C). (Matys V, etal. 2006. TRANSFAC and its module TRANSCompel: transcriptional generegulation in eukaryotes. Nucleic Acids Res 34 (Databaseissue):D108-110; Hertz G Z and Stormo G D. 1999. Identifying DNA andprotein patterns with statistically significant alignments of multiplesequences. Bioinformatics 15:563-577.) Those 13 genes and the proteinsthey encode are listed in Table B. These findings suggest thatover-expression of ATF4 is sufficient to recapitulate a component of theairway gene-expression differences associated with the presence of COPDin vivo, and that ATF4 might therefore be a mediator of these changes.

TABLE 6 Enrichment of transcription factor binding sites among bronchialairway gene expression changes associated with COPD. TranscriptionGATHER Genes from COPD Bayes factor annotation signature P-value FactorActivating V$ATF4_Q2 FOS <0.001 6 transcription GABRP factor 4 (ATF4)IRAK3 MIA MTNR1A NR4A1 PLA2G4A SLIT2 UGT1A10 WIF1 cAMP V$CREB_Q2_01ABCA12 <0.001 6 responsive ACAA2 binding element DKFZP564O0823 1 (CREB1)EPB41L2 FOS GRP IRAK3 MIA MUC13 NR4A1 PTGS2 SRPX2 UGT1A10

TABLE B Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number  3934_at LCN2 3934 45142  2353_at FOS 2353 27 125  1847_at DUSP5 1847 20 118  9982_at FGFBP19982 98 195  5743_at PTGS2 5743 68 165  3371_at TNC 3371 39 137 10643_atIGF2BP3 10643 7 105  6289_at SAA2 6289 72 169 26154_at ABCA12 26154 33131  1836_at SLC26A2 1836 19 117  629_at CFB 629 73 170 11213_at IRAK311213 10 108  6288_at SAA1 6288 71 168

EXAMPLE 4 The Relationship Between COPD-Associated Gene Expression inthe Bronchial Airway Epithelium and in Lung Parenchyma

We next examined whether COPD-associated gene expression changes in thebronchial airway reflect disease-associated processes in lungparenchyma. By GSEA, we found concordant enrichment of gene expressionchanges in bronchial airway and lung tissue in three previouslypublished COPD datasets (FDR_(GSEA)<0.05) (FIG. 7). Genes whoseexpression levels were increased in the lung tissue of GOLD Grade 2subjects compared to GOLD Grade 0 subjects (Ning W, et al. 2004.Comprehensive gene expression profiles reveal pathways related to thepathogenesis of chronic obstructive pulmonary disease. Proc Natl AcadSci USA 101:14895-14900.) or negatively correlated with FEF_(25-75%)(Wang I M, et al. 2008. Gene Expression Profiling in Patients withChronic Obstructive Pulmonary Disease and Lung Cancer. Am J Respir CritCare Med 177:411.) were enriched among genes whose expression wasincreased in the bronchial airway with COPD. Similarly, genesdown-regulated in the lung tissue of COPD cases compared to controls orin lung tissue from subjects with worse lung function were enrichedamong genes whose expression was decreased in the bronchial airwayepithelium in COPD. (Bhattacharya S, et al. 2009. Molecular biomarkersfor quantitative and discrete COPD phenotyes. Am J Respir Cell Mol Biol40:359-367.) There were also similarities between COPD-associated airwaygene expression and lung parenchymal gene expression when geneexpression profiles from these previously published datasets were rankedaccording to the strength of association with COPD or COPD-relatedtraits (FDR_(GSEA)<0.05) (FIG. 3) and interrogated with thedisease-associated genes we identified in the bronchial airway. Thesefindings demonstrate that similar changes in gene expression occur inthe airway epithelium and lung tissue, suggesting that theCOPD-associated airway gene expression differences mirror aspects ofdisease processes occurring in lung tissue. This finding validates theuse of the expression of these 98 genes in airway epithelium as a markerof disease state in lung tissue.

To further explore the relationship between bronchial epithelial andlung tissue gene expression related to COPD, we used GSEA to examine thedistribution of the 98 genes whose expression levels were associatedwith COPD in a ranking of all genes according to their expression changein lung parenchyma as a function of mean linear intercept, a morphologicmeasure of emphysema (GSE27597). (Campbell J D, et al. 2012. A geneexpression signature of emphysema-related lung destruction and itsreversal by the tripeptide GHK. Genome Med 4:67.) Lung parenchymal geneswhose expression levels increased with regional emphysema severity wereenriched for bronchial epithelial genes whose expression was increasedin COPD (FDR_(GSEA)<0.05) (FIG. 8). The genes contributing most stronglyto this enrichment included SERPINB13, a serine peptidase inhibitor, andTMPRSS11D, a trypsin-like protease. The full list of identified genesand encoded proteins is presented in Table C. These findings support thebiologic relevance of the bronchial epithelial gene expression signatureof COPD by linking it to both clinical and pathologic measures ofdisease severity.

TABLE C Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number  5275_at SERPINB13 527556 153  4585_at MUC4 4585 53 150  7348_at UPK1B 7348 81 178  2353_at FOS2353 27 125  23120_at ATP10B 23120 26 124 131450_at CD200R1 131450 12110  8190_at MIA 8190 92 189  2568_at GABRP 2568 30 128   629_at CFB 62973 170  1825_at DSC3 1825 18 116  1562_at CYP2C18 1562 14 112 400986_atLOC400986 400986 46 143  26154_at ABCA12 26154 33 131  56938_at ARNTL256938 66 163  56667_at MUC13 56667 64 161  84419_at C15orf48 84419 87184  56169_at GSDMC 56169 63 160  9407_at TMPRSS11D 9407 96 193  9245_atGCNT3 9245 94 191

Genes (and encoded proteins) that are in common to tables B and C arelisted in Table D.

TABLE D Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number 26154_at ABCA12 26154 33131  629_at CFB 629 73 170  2353_at FOS 2353 27 125

EXAMPLE 5 Reversibility of COPD-Associated Changes in Airway EpithelialGene Expression with Treatment

Because inhaled corticosteroids are commonly used to treat COPD, we nextsought to determine whether COPD-associated changes in airway geneexpression were modifiable by fluticasone therapy in patients with COPD.We used GSEA to examine the expression of the bronchial epithelial COPDsignature in a ranking of gene expression profiles derived frombronchial biopsies obtained from a subset of subjects from the GLUCOLDtrial (ClinicalTrials.gov registration number: NCT00158847) (GSE36221),an independent longitudinal study of subjects with COPD randomized tofluticasone with or without salmeterol, or placebo. (Lapperre T S, etal, and Groningen Leiden Universities Corticosteroids in ObstructiveLung Disease Study Group. 2009. Effect of fluticasone with and withoutsalmeterol on pulmonary outcomes in chronic obstructive pulmonarydisease: a randomized trial. Ann Intern Med 151:517-527.) Expressionlevels of the 54 genes increased in the bronchial epithelial COPDsignature were enriched among genes whose expression decreased followingtreatment containing fluticasone (FDR_(GSEA)<0.05, FIG. 9A). Similarly,expression levels of the 44 genes decreased with COPD in the bronchialairway signature were enriched among genes whose expression levelsincreased following treatment with fluticasone in the GLUCOLD cohort(FDR_(GSEA)<0.05, FIG. 9A). The genes contributing most strongly to thethis enrichment included DUSPS, a key regulator of cell proliferationand differentiation, TMPRSS11D, which serves a key role in host defensein the airway, and CLDN8, which functions in tight junctions betweenepithelial cells (FIG. 9B). These results suggest that a subset ofairway gene expression changes associated with COPD can be reversed byinhaled corticosteroids.

The genes contributing most strongly to significant GSEA enrichment ofthe 98-gene COPD signature among the GLUCOLD dataset (“core enrichmentgenes”) are listed in Table E.

TABLE E Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number  56667_at MUC13 56667 64161  1847_at DUSP5 1847 20 118  5172_at SLC26A4 5172 55 152  56938_atARNTL2 56938 66 163  4585_at MUC4 4585 53 150 131450_at CD200R1 13145012 110  1048_at CEACAM5 1048 6 104 135228_at CD109 135228 13 111 5743_at PTGS2 5743 68 165  7348_at UPK1B 7348 81 178  3371_at TNC 337139 137 440603_at BCL2L15 440603 51 148  1825_at DSC3 1825 18 116 54575_at UGT1A10 54575 59 156  56169_at GSDMC 56169 63 160  2571_atGAD1 2571 31 129  1562_at CYP2C18 1562 14 112  4543_at MTNR1A 4543 52149  23120_at ATP10B 23120 26 124  10643_at IGF2BP3 10643 7 105  5275_atSERPINB13 5275 56 153  27286_at SRPX2 27286 34 132  7850_at IL1R2 785082 179  26154_at ABCA12 26154 33 131  2568_at GABRP 2568 30 128  9407_atTMPRSS11D 9407 96 193 117156_at SCGB3A2 117156 11 109   552_at AVPR1A552 61 158 389136_at VGLL3 389136 44 141  4256_at MGP 4256 50 147 8910_at SGCE 8910 92 189  10455_at PECI 10455 5 103  23089_at PEG1023089 25 123 404220_at C6orf201 404220 48 145  10391_at CORO2B 10391 3101  9353_at SLIT2 9353 95 192  79625_at C4orf31 79625 83 180  80206_atFHOD3 80206 85 182  10449_at ACAA2 10449 4 102  2565_at GABRG1 2565 29127  2037_at EPB41L2 2037 21 119 221395_at GPR116 221395 24 122  4883_atNPR3 4883 54 151  9723_at SEMA3E 9723 97 194 158471_at PRUNE2 158471 15113  8471_at IRS4 8471 88 185  64759_at TNS3 64759 76 173  9073_at CLDN89073 93 190  7092_at TLL1 7092 79 176 342035_at GLDN 342035 40 138 10321_at CRISP3 10321 2 100  5737_at PTGFR 5737 67 164

To validate our findings in the GLUCOLD cohort, we examined therelationship between the airway gene expression signature of COPD andfluticasone-related gene expression differences from an independentdataset in which gene expression in bronchial epithelium samples frombefore and after fluticasone treatment was profiled using microarrays.(Woodruff P G, et al. 2007. Genome-wide profiling identifies epithelialcell genes associated with asthma and with treatment response tocorticosteroids. Proc Natl Acad Sci USA 104:15858-15863.) Using a linearmixed effects model, genes were ranked according to their change withfluticasone over time. Using GSEA, we found that the 54 genesup-regulated in the airway COPD signature were enriched among the genesdecreased by fluticasone treatment and that the 44 genes down-regulatedin the airway COPD signature were enriched among the genes increased byfluticasone treatment (FDR_(GSEA)<0.05, FIG. 10). This finding suggeststhat fluticasone reverts genes that are altered in the airways ofpatients with COPD. Taken together with our observations in the GLUCOLDcohort, these data suggest that COPD-associated gene expression patternsare potentially dynamic with therapy.

Table F lists genes (and corresponding proteins) in common betweenTables B and E.

TABLE F Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number 26154_at ABCA12 26154 33131  1847_at DUSP5 1847 20 118 10643_at IGF2BP3 10643 7 105  5743_atPTGS2 5743 68 165  1836_at SLC26A2 1836 19 117  3371_at TNC 3371 39 137

Table G lists genes (and corresponding proteins) in common betweenTables C and E.

TABLE G Gene Protein Sequence Sequence Gene Entrez Gene IdentificationIdentification Probe ID Symbol ID Number Number  26154_at ABCA12 2615433 131  56938_at ARNTL2 56938 66 163  23120_at ATP10B 23120 26 124131450_at CD200R1 131450 12 110  1562_at CYP2C18 1562 14 112  1825_atDSC3 1825 18 116  2568_at GABRP 2568 30 128  56169_at GSDMC 56169 63 160 56667_at MUC13 56667 64 161  4585_at MUC4 4585 53 150  5275_atSERPINB13 5275 56 153  9407_at TMPRSS11D 9407 96 193  7348_at UPK1B 734881 178

Discussion

By performing whole genome gene-expression profiling of bronchialbrushings in a study of individuals with and without COPD, we haveidentified a COPD-related bronchial airway field of injury that isdefined by gene expression alterations and has several importantcharacteristics. Firstly, the gene-expression alterations in this fieldof injury are associated both with COPD and continuous COPD-relatedmeasures of lung function. Secondly, the COPD-associated gene expressionfield of injury measured in the bronchial airway epithelium is similarto COPD-associated gene-expression differences occurring in lungparenchyma. Thirdly, the COPD-associated gene expression field of injuryis modifiable with treatment.

We have validated the COPD-associated airway-epithelium gene expressiondifferences we identified, by comparison to a number of previouslypublished studies including one study of small-airway gene expression(Tilley A E, et al. 2009. Down-regulation of the Notch pathway in humanairway epithelium in association with smoking and chronic obstructivepulmonary disease. Am J Respir Crit Care Med 179:457-466.), and sixstudies of lung parenchyma. (Spira A, et al. 2004. Gene ExpressionProfiling of Human Lung Tissue from Smokers with Severe Emphysema. Am JRespir Cell Mol Biol 31:601-610; Golpon H A, et al. 2004. Emphysema LungTissue Gene Expression Profiling. Am J Respir Cell Mol Biol 31:595-600;Ning W, et al. 2004. Comprehensive gene expression profiles revealpathways related to the pathogenesis of chronic obstructive pulmonarydisease. Proc Natl Acad Sci USA 101:14895-14900; Bhattacharya S, et al.2009. Molecular biomarkers for quantitative and discrete COPD phenotyes.Am J Respir Cell Mol Biol 40:359-367; Wang I M, et al. 2008. GeneExpression Profiling in Patients with Chronic Obstructive PulmonaryDisease and Lung Cancer. Am J Respir Crit Care Med 177:411; Campbell JD, et al. 2012. A gene expression signature of emphysema-related lungdestruction and its reversal by the tripeptide GHK. Genome Med 4:67.)These observations suggest a reliable COPD-associated pattern of geneexpression in the bronchial airway that is similar to distalCOPD-associated gene expression differences. While the COPD-associatedgene expression similarities between the bronchial airway and whole lungtissue could be due to similarities between the bronchial airway andeither the lung parenchyma and/or the terminal bronchioles, our datasuggest that the accessible bronchial airways reflect disease-associatedprocesses occurring deep in the lung. Importantly, many of the previousstudies of COPD-associated gene expression have involved lung tissuethat is adjacent to lung cancer. In this study, by leveragingbronchoscopy samples from a lung-cancer screening cohort where theprevalence of cancer is low, we were able to profile samples exclusivelyfrom a large number of patients without lung cancer. Taken together,these findings demonstrate that the bronchial airway can serve as areadily accessible biospecimen to measure COPD-related processes in bothresearch and clinical settings, thus enabling the systems, methods, andother aspects of the inventions of this disclosure.

The two major sites of COPD-associated pathology are the alveolae andthe terminal bronchioles. We measured gene expression in much moreproximal airways. If the major site of disease is more distal in thelung, there is no reason that gene expression should be altered at sitesremoved from the sites of pathology. The existence of an airway field ofinjury in COPD is an unexpected and exciting finding. Until this study,the airway field of injury concept has been described in severalmalignant diseases (initially oral cancer in the 1950s, subsequentlylung cancer, and also some non-pulmonary cancers like breast cancer).However, this is the first study to demonstrate an airway field ofinjury (gene expression in the airway epithelium involved in diseasethat is similar to gene expression changes in distal diseased lungtissue) in a non-malignant lung disease.

The specific genes within the COPD airway epithelial gene expressionsignature support the biologic plausibility of this signature. Forexample, TMPRSS11D, also called human airway trypsin-like protease,localizes to ciliated bronchial epithelial cells and was first isolatedfrom the sputum of patients with chronic airway diseases. (Takahashi M,et al. 2001. Localization of human airway trypsin-like protease in theairway: an immunohistochemical study. Histochem Cell Biol 115:181-187.)The increased levels of TMPRSS11D gene expression in the airwayepithelium of individuals with COPD are consistent with the hypothesisthat this protein plays a key role in the biologic defense againstinhaled substances (Takahashi M, et al. 2001. Localization of humanairway trypsin-like protease in the airway: an immunohistochemicalstudy. Histochem Cell Biol 115:181-187.) SERPINB13 is a serine peptidaseinhibitor increased in both airway and lung parenchyma in associationwith COPD. Our finding that both TMPRSS11D and SERPINB13 are increasedin the airway of patients with COPD and our finding that these genes aredecreased with fluticasone suggests the protease/anti-protease imbalancethat is thought to play a key role in COPD pathogenesis is alsoreflected in airway epithelial cells, and that restoration of thisbalance could be useful for monitoring response to COPD therapies suchas inhaled corticosteroids. Prostaglandin-endoperoxidase synthase 2(PTGS2), is a pro-inflammatory mediator increased in the bronchialairway of individuals with COPD and is a potential target for novelanti-inflammatory therapies. Claudin 8 (CLDN8) is a member of theclaudin family, which plays a key role in tight junctions andparacellular permeability. (Lal-Nag M and Morin P J. 2009. The claudins.Genome Biol 10:235.) Our finding that CLDN8 is decreased in the airwayepithelium of subjects with COPD and increased after treatment withfluticasone suggests a potentially reversible impairment in the airwayepithelium's critical barrier function (Heijink I H, et al. 2010.Characterization of cell adhesion in airway epithelial cell types usingelectric cell-substrate impedance sensing. Eur Respir J 35:894-903), andthis finding is consistent with the previously observed down-regulationof claudins and other tight junction genes in bronchial epithelial cellsfrom smokers with COPD. (Shaykhiev R, et al. 2011. Cigarette smokingreprograms apical junctional complex molecular architecture in the humanairway epithelium in vivo. Cell Mol Life Sci 68:877-892; Soini Y. 2011.Claudins in lung diseases. Respir Res 12:70.)

Our observations about the potential role of ATF4 in mediatingCOPD-associated gene expression differences in bronchial epithelium isintriguing given the role of ATF4 in mediating the unfolded proteinresponse. (Wek R C and Cavener D R. 2007. Translational control and theunfolded protein response. Antioxid Redox Signal 9:2357-2371; Rzymski T,Milani M, Singleton D C, and Harris A L. 2009. Role of ATF4 inregulation of autophagy and resistance to drugs and hypoxia. Cell Cycle8:3838-3847.) ER stress from acute cigarette smoke exposure leads to anunfolded protein response which is proposed to play a role in thedevelopment of COPD. (Kelsen S G, et al. 2008. Cigarette smoke inducesan unfolded protein response in the human lung: a proteomic approach. AmJ Respir Cell Mol Biol 38:541-550; Geraghty P, et al. 2011. Induction ofthe unfolded protein response by cigarette smoke is primarily anactivating transcription factor 4-C/EBP homologous protein mediatedprocess. International Journal of COPD 6:309-319.) An increase in ERstress markers has been described in the lungs of patients with COPD.(Malhotra D, et al. 2009. Heightened endoplasmic reticulum stress in thelungs of patients with chronic obstructive pulmonary disease: the roleof Nrf2-regulated protesasomal activity. Am J Respir Crit Care Med180:1196-1207), and administration of acrolein, an aldehyde in cigarettesmoke, leads to an increase in ER stress markers and airspaceenlargement in mice, suggesting that ER stress and the unfolded proteinresponse play key roles in the development of emphysema. (Kitaguchi Y,et al. Acrolein induces endoplasmic reticulum stress and causes airspaceenlargement. PLoS ONE 7:e38038.) This is the first study to ourknowledge to identify ATF4-driven gene expression differences inindividuals with COPD. We have validated predicted targets of ATF4 inthe airway COPD signature, and have further demonstrated significantenrichment of genes increased in the airway COPD signature among genesincreased by ATF4. While we identified this potential regulatoryrelationship in airway epithelium, further studies will be necessary toexamine the extent of this response in lung tissue and its importancefor disease development.

The potential clinical relevance of the COPD-associated field of injuryis supported by its reversal with inhaled corticosteroids in the GLUCOLDcohort. (Lapperre T S, et al, and Groningen Leiden UniversitiesCorticosteroids in Obstructive Lung Disease Study Group. 2009. Effect offluticasone with and without salmeterol on pulmonary outcomes in chronicobstructive pulmonary disease: a randomized trial. Ann Intern Med151:517-527.) This aspect of the airway signature of COPD indicates thatthe constituent gene expression differences reflect more thandifferences due to demographic or smoking-related factors, but rather anaspect of the disease process that is modifiable with therapy. Moreover,further studies should be conducted to determine whether heterogeneityin the extent to which the airway signature of COPD is reversed bytherapy is associated with differences in the clinical benefit obtainedby patients. Similarly, it will be important to determine whethergene-expression heterogeneity among patients with COPD reflectsunderlying biological differences that can be used to develop markersthat predict aspects of the clinical heterogeneity of COPD such astherapeutic response or rate of lung function decline.

As with other distal lung diseases, there are a number of potentialmechanisms that might account for the similarity between lung tissue andbronchial airway gene expression. (Steiling K, et al. 2008. The field oftissue injury in the lung and airway. Cancer Prey Res 1:396-403.) TheCOPD-associated transcriptomic alterations may reflect, in part,specific physiologic responses to the toxins in cigarette smoke that inturn contribute to COPD pathogenesis. The relationship between theairway signature of COPD and gene expression differences associated withregional emphysema severity within an individual, as well as thereversal of the signature following therapy, suggest that the etiologyof the COPD-associated gene expression differences is not solely due toan individual's physiologic response to tobacco smoke.

Other potential mechanisms for the airway field of injury are related tocell-cell communication. For example, inflammatory cells recruited intothe airway and lungs of smokers with COPD and the cytokines they producemay induce gene-expression alterations throughout the airway epithelium.This hypothesis is consistent with our finding of specificinflammatory-related pathways enriched among the genes in our signature(FIG. 2; Table 4). However, in silico analysis of white bloodcell-specific gene-expression in these samples did not revealsignificant proportions of inflammatory cells nor differences in theproportion of inflammatory cells in smokers with and without COPD, andthus we do not believe that our signature directly reflects changingnumbers of inflammatory cells within our airway brushings in individualswith COPD. Nonetheless, infiltration of the airway wall withinflammatory cells in smokers with COPD (Lapperre T S, et al, andGroningen Leiden Universities Corticosteroids in Obstructive LungDisease Study Group. 2009. Effect of fluticasone with and withoutsalmeterol on pulmonary outcomes in chronic obstructive pulmonarydisease: a randomized trial. Ann Intern Med 151:517-527) could producechanges in the adjacent epithelial layer lining that airway.

Through analysis of the largest cohort of bronchial airway geneexpression in COPD, we have identified a COPD-associated airway field ofinjury despite a number of potentially important limitations to ourstudy design. Due to the nature of this lung cancer screening cohort,characterization of COPD-related phenotypes was limited, and we definedCOPD as airflow obstruction on pre-bronchodilator spirometry. However,the similarity with previously published lung tissue gene expressiondatasets demonstrates that these COPD-associated changes in bronchialairway gene expression are reproducible and reflective of diseaseactivity. While spirometry remains the standard for diagnosing COPD(Global initiative for chronic obstructive lung disease. 2011. Globalinitiative for chronic obstructive lung disease: Global strategy for thediagnosis, management, and prevention of chronic obstructive pulmonarydisease.), the association of airway gene expression with sub-phenotypesof COPD was not evaluated including quantitative imaging of airwayremodeling and emphysema, gas transfer capacity, chronic bronchitis,previous respiratory illness, frequency of exacerbations and/or qualityof life metrics. Given the clinical heterogeneity among smokers withCOPD, it is possible that different clinical subphenotypes of diseasewill impact airway gene expression differently and might contribute tothe heterogeneity seen in the gene-expression signature. Furthermore,given that we were leveraging a bronchoscopy-based cohort for this studyin which the majority of subjects with COPD had mild to moderatedisease, it is unclear if our findings will generalize to smokers withlater stage disease or if there are alterations specific to more severedisease. However, the enrichment of our airway gene expression signatureamong genes that change with regional emphysema severity in the lungs ofsmokers with severe COPD suggests that our gene expression signature isalso relevant in more severe disease. Finally, whilefluticasone-containing therapy has not been consistently linked with aclinical benefit, the decrease in the COPD airway gene expressionsignature following fluticasone therapy in two independent cohortssuggests that the COPD-associated airway field of injury is not a staticconsequence of disease but rather is dynamic.

In summary, we have shown that COPD induces a field of injury thatextends from the lung parenchyma into the bronchial airway, and thatsome of the COPD-associated alterations in airway gene expression may bemediated by ATF4. We have also shown that a subset of theseCOPD-associated airway gene expression changes is reversed byfluticasone in a COPD cohort where that treatment resulted inimprovement in lung function. These data demonstrate that geneexpression profiling of the airway epithelium, which can be sampled viabronchoscopy, serves as a surrogate biomarker of disease activity. Thesefindings suggest that this field of injury in COPD extends to epithelialcells that can be more readily sampled from the nose. (Zhang X, et al.2010. Similarities and differences between smoking-related geneexpression in the nasal and bronchial epithelium. Physiol Genomics41:1-8.).

1. A method of classifying the chronic obstructive pulmonary disease(COPD) status of a subject, comprising: (a) providing a tissue sampleobtained from respiratory tract epithelium of the subject; (b)determining the expression level of at least one transcript comprising(i) a sequence as set forth in any one of SEQ ID NOS. 1 to 98, (ii) afragment of at least 100 nucleotides of a sequence as set forth in anyone of SEQ ID NOS. 1 to 98, or (iii) a sequence with substantialhomology to (i) or (ii), in the tissue sample to provide an expressionpattern profile; (c) comparing the expression pattern profile with areference expression pattern profile; and (d) classifying the COPDstatus of the subject based on the comparing.
 2. The method of claim 1,wherein the tissue sample is a tissue sample obtained from the bronchiwalls of at least one of sixth generation, seventh generation, andeighth generation bronchi of the subject.
 3. The method of claim 1,wherein the tissue sample is obtained during fiberoptic bronchoscopy bybrushing the bronchi walls of the subject.
 4. The method of claim 1,wherein the at least one transcript is a transcript that is upregulatedin COPD and is selected from SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8,SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO:16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ IDNO: 22, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35,SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 42, SEQ ID NO:43, SEQ ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 52, SEQ IDNO: 53, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 59, SEQID NO: 63, SEQ ID NO: 64, SEQ ID NO: 65, SEQ ID NO: 66, SEQ ID NO: 68,SEQ ID NO: 71, SEQ ID NO: 72, SEQ ID NO: 73, SEQ ID NO: 74, SEQ ID NO:78, SEQ ID NO: 81, SEQ ID NO: 82, SEQ ID NO: 84, SEQ ID NO: 86, SEQ IDNO: 87, SEQ ID NO: 94, SEQ ID NO: 96, and SEQ ID NO:
 98. 5. The methodof claim 1, wherein the at least one transcript is a transcript that isdownregulated in COPD and is selected from SEQ ID NO: 1, SEQ ID NO: 2,SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 9, SEQ ID NO: 11,SEQ ID NO: 15, SEQ ID NO: 21, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO:25, SEQ ID NO: 29, SEQ ID NO: 36, SEQ ID NO: 40, SEQ ID NO: 41, SEQ IDNO: 44, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, SEQ ID NO: 50, SEQID NO: 54, SEQ ID NO: 58, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62,SEQ ID NO: 67, SEQ ID NO: 69, SEQ ID NO: 70, SEQ ID NO: 75, SEQ ID NO:76, SEQ ID NO: 77, SEQ ID NO: 79, SEQ ID NO: 80, SEQ ID NO: 83, SEQ IDNO: 85, SEQ ID NO: 88, SEQ ID NO: 89, SEQ ID NO: 90, SEQ ID NO: 91, SEQID NO: 92, SEQ ID NO: 93, SEQ ID NO: 95, SEQ ID NO:
 97. 6. The method ofclaim 1, comprising determining the expression level of at least tentranscripts, each comprising (i) a sequence as set forth in any one ofSEQ ID NOS. 1 to 98, (ii) a fragment of at least 100 nucleotides of asequence as set forth in any one of SEQ ID NOS. 1 to 98, or (iii) asequence with substantial homology to (i) or (ii), in the tissue sampleto provide the expression pattern profile.
 7. The method of claim 1,comprising determining the expression level of at least 98 transcripts,each comprising (i) a sequence as set forth in any one of SEQ ID NOS. 1to 98, (ii) a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS. 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii), in the tissue sample to provide theexpression pattern profile.
 8. The method of claim 1, wherein anincreased relative level of expression of the at least one transcript inthe respiratory tract epithelium sample of the subject, a decreasedrelative level of the at least one transcript in the bronchi sample ofthe subject, or a combination thereof is used to classify the COPD. 9.The method of claim 1, wherein the COPD status of the subject isclassified as to the extent of at least one of airflow obstruction,emphysematous descruction of lung parenchyma, and small airwayinflammation in the subject.
 10. The method of claim 1, wherein the COPDstatus of the subject is classified as the the likelihood of diseaseprogression.
 11. The method of claim 1, wherein the COPD status of thesubject is classified as to current disease severity.
 12. The method ofclaim 1, wherein the COPD status of the subject is classified as to thelikelihood of a positive clinical response to treatment with ananti-COPD therapeutic agent.
 13. The method of claim 1, wherein the COPDstatus of the subject is classified as to the clinical response of thesubject to treatment with an anti-COPD therapeutic agent.
 14. The methodof claim 1, wherein the expression level of the at least one transcriptis determined by a process comprising a method selected from RT-PCR,Northern blotting, ligase chain reaction, and array hybridization. 15.The method of claim 1, further comprising measuring the expression levelof at least one control nucleic acid in the tissue sample.
 16. Themethod of claim 1, wherein the expression level of the at least onetranscript is determined by a process comprising pattern recognition.17. The method of claim 16, wherein the process comprising patternrecognition comprises a linear combination of expression levels of thetarget transcripts.
 18. The method of claim 16, wherein the processcomprising pattern recognition comprises a nonlinear combination ofexpression levels of the target sequences.
 19. The method of claim 17,wherein the process comprising pattern recognition comprises a nonlinearcombination of expression levels of the target sequences.
 20. A systemfor expression-based classification of COPD disease status, the systemcomprising at least one polynucleotide capable of specificallyhybridizing to a RNA transcript comprising (i) a sequence as set forthin any one of SEQ ID NOS. 1 to 98, (ii) a fragment of at least 100nucleotides of a sequence as set forth in any one of SEQ ID NOS. 1 to98, (iii) a sequence with substantial homology to (i) or (ii), or (iv) asequence that is the complement of a sequence according to any one of(i) to (iii).
 21. The system of claim 20, wherein the at least onepolynucleotide comprising at least one polynucleotide probe for thedetection of the transcript.
 22. The system of claim 20, wherein the atleast one polynucleotide comprises at least one primer pair capable ofamplifying a portion of the RNA transcript.
 23. The system of claim 20,wherein the system comprises polynucleotides comprising sequences as setforth in SEQ ID NOs: 1, 2, 3, 4, 5, 6, 7, 8, 9 and
 10. 24. The systemaccording to claim 20, wherein the system comprises at least 5polynucleotides.
 25. The system according to claim 20, wherein thesystem comprises at least 10 polynucleotides.
 26. The system of claim20, wherein the at least one polynucleotide comprises a sequencecorresponding to one or more nucleic acid molecules selected from: (a) anucleic acid depicted in any one of SEQ ID NOs: 1-98; (b) an RNA form ofany one of the nucleic acids depicted in SEQ ID NOs: 1-98; (c) a peptidenucleic acid form of any one of the nucleic acids depicted in SEQ IDNOs: 1-98; (d) a nucleic acid comprising at least 20 consecutive basesof any of (a-c); (e) a nucleic acid comprising at least 25 consecutivebases having at least 90% sequence identity to any of (a-c); and (f) acomplement to any of (a-e).
 27. A method of treating COPD in a subjectin need thereof, comprising: (a) providing a tissue sample obtained fromthe respiratory tract epithelium of the subject; (b) determining theexpression level of at least one transcript comprising (i) a sequence asset forth in any one of SEQ ID NOS. 1 to 98, (ii) a fragment of at least100 nucleotides of a sequence as set forth in any one of SEQ ID NOS. 1to 98, or (iii) a sequence with substantial homology to (i) or (ii), inthe tissue sample to provide an expression pattern profile; (c)comparing the expression pattern profile with a reference expressionpattern profile; (d) classifying the COPD status of the subject based onthe comparing; (e) administering an anti-COPD therapeutic agent to thesubject if the subject is classified as having active COPD diseasestatus warranting therapeutic intervention; and (f) not administering ananti-COPD therapeutic agent to the subject if the subject is classifiedas not having active COPD disease status warranting therapeuticintervention.
 28. The method of claim 27, wherein the tissue sample is atissue sample obtained from the bronchi walls of at least one of sixthgeneration, seventh generation, and eighth generation bronchi of thesubject.
 29. The method of claim 27, wherein the tissue sample isobtained during fiberoptic bronchoscopy by brushing the bronchi walls ofthe subject.
 30. The method of claim 27, wherein the at least onetranscript is a transcript that is upregulated in COPD and is selectedfrom SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 10, SEQ ID NO:12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 16, SEQ ID NO: 17, SEQ IDNO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 22, SEQ ID NO: 26, SEQID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32,SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 37, SEQ ID NO:38, SEQ ID NO: 39, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 45, SEQ IDNO: 46, SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 55, SEQID NO: 56, SEQ ID NO: 57, SEQ ID NO: 59, SEQ ID NO: 63, SEQ ID NO: 64,SEQ ID NO: 65, SEQ ID NO: 66, SEQ ID NO: 68, SEQ ID NO: 71, SEQ ID NO:72, SEQ ID NO: 73, SEQ ID NO: 74, SEQ ID NO: 78, SEQ ID NO: 81, SEQ IDNO: 82, SEQ ID NO: 84, SEQ ID NO: 86, SEQ ID NO: 87, SEQ ID NO: 94, SEQID NO: 96, and SEQ ID NO:
 98. 31. The method of claim 27, wherein the atleast one transcript is a transcript that is downregulated in COPD andis selected from SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4,SEQ ID NO: 5, SEQ ID NO: 9, SEQ ID NO: 11, SEQ ID NO: 15, SEQ ID NO: 21,SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 29, SEQ ID NO:36, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 44, SEQ ID NO: 47, SEQ IDNO: 48, SEQ ID NO: 49, SEQ ID NO: 50, SEQ ID NO: 54, SEQ ID NO: 58, SEQID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 67, SEQ ID NO: 69,SEQ ID NO: 70, SEQ ID NO: 75, SEQ ID NO: 76, SEQ ID NO: 77, SEQ ID NO:79, SEQ ID NO: 80, SEQ ID NO: 83, SEQ ID NO: 85, SEQ ID NO: 88, SEQ IDNO: 89, SEQ ID NO: 90, SEQ ID NO: 91, SEQ ID NO: 92, SEQ ID NO: 93, SEQID NO: 95, SEQ ID NO:
 97. 32. The method of claim 27, comprisingdetermining the expression level of at least ten transcripts, eachcomprising (i) a sequence as set forth in any one of SEQ ID NOS. 1 to98, (ii) a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS. 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii), in the tissue sample to provide theexpression pattern profile.
 33. The method of claim 27, comprisingdetermining the expression level of at least 98 transcripts, eachcomprising (i) a sequence as set forth in any one of SEQ ID NOS. 1 to98, (ii) a fragment of at least 100 nucleotides of a sequence as setforth in any one of SEQ ID NOS. 1 to 98, or (iii) a sequence withsubstantial homology to (i) or (ii), in the tissue sample to provide theexpression pattern profile.
 34. The method of claim 27, wherein anincreased relative level of expression of the at least one transcript inthe bronchi sample of the subject, a decreased relative level of the atleast one transcript in the bronchi sample of the subject, or acombination thereof is used to classify the COPD.
 35. The method ofclaim 27, wherein the COPD status of the subject is classified as to theextent of at least one of airflow obstruction, emphysematous descructionof lung parenchyma, and small airway inflammation in the subject. 36.The method of claim 27, wherein the COPD status of the subject isclassified as the the likelihood of disease progression.
 37. The methodof claim 27, wherein the COPD status of the subject is classified as tocurrent disease severity.
 38. The method of claim 27, wherein the COPDstatus of the subject is classified as to the likelihood of a positiveclinical response to treatment with an anti-COPD therapeutic agent. 39.The method of claim 27, wherein the COPD status of the subject isclassified as to the clinical response of the subject to treatment withan anti-COPD therapeutic agent.
 40. The method of claim 27, wherein theexpression level of the at least one transcript is determined by aprocess comprising a method selected from RT-PCR, Northern blotting,ligase chain reaction, and array hybridization.
 41. The method of claim27 further comprising measuring the expression level of at least onecontrol nucleic acid in the tissue sample.
 42. The method of claim 27,wherein the expression level of the at least one transcript isdetermined by a process comprising pattern recognition.
 43. The methodof claim 42, wherein the process comprising pattern recognitioncomprises a linear combination of expression levels of the targettranscripts.
 44. The method of claim 42, wherein the process comprisingpattern recognition comprises a nonlinear combination of expressionlevels of the target sequences.
 45. The method of claim 43, wherein theprocess comprising pattern recognition comprises a nonlinear combinationof expression levels of the target sequences.
 46. The method of claim27, wherein the anti-COPD therapeutic agent is fluticasone.